Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: EARLY SURVEY WITH BIBLIOMETRIC ANALYSIS ON MACHINE LEARNING APPROACHES IN CONTROLLING COVID-19 OUTBREAKS
Review round: 1
Reviewer: 1

Output:
Basic reporting: No comment
Experimental design: No comment
Validity of the findings: No comment
Additional comments: Machine learning is one important technique tool to fight the COVID-19 pandemic. As done in this manuscript, to give a early survey with bibliometric analysis is necessary and meaningful. It has not been done previously. The contents in this manuscript are rich. The representations are logical and structured. The listed challenges and future research opportunities are insightful.

There are several comments.

1. The title of Section 6. General Discussions is not appropriate. This part should be the main contents or results of this manuscript. I suggest use the title of "Survey and the bibliometric analysis".

2. Some references are missing.
[1]	D. Dong, Z. Tang, S. Wang, et al., The role of imaging in the detection and management of COVID-19: a review. IEEE Reviews in Biomedical Engineering, 2020, DOI: 10.1109/RBME.2020.2990959.
[2]	F. Shi, J. Wang, J. Shi, et al., Review of Artificial Intelligence Techniques in Imaging Data Acquisition, Segmentation and Diagnosis for COVID-19, IEEE Reviews in Biomedical Engineering, 2020, DOI: 10.1109/RBME.2020.2987975.
[3]	Rahaman, Md Mamunur et al. ‘Identification of COVID-19 Samples from Chest X-Ray Images Using Deep Learning: A Comparison of Transfer Learning Approaches’. 1 Jan. 2020 : 1 – 19.


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: EARLY SURVEY WITH BIBLIOMETRIC ANALYSIS ON MACHINE LEARNING APPROACHES IN CONTROLLING COVID-19 OUTBREAKS
Review round: 1
Reviewer: 2

Output:
Basic reporting: The paper presents a review for COVID19 detection and diagnosis techniques. The manuscript however lacks readability criterion. There are plenty of information that is not required which makes the reader inconclusive about the study. Therefore, it is suggested for authors to reconsider the approach in order to make it more readable and significant for the research community.
The whole manuscript requires a thorough proof reading. There are plenty of punctuation and grammar mistakes. For example sentence on line 83 to 88 is a one big sentence. It needs to be divided into small and simpler sentences. Moreover the “COVID-19” is repeated 9 times in the same sentence.
The structure of the survey presented in Figure 1 need to be more concise. For example what is the difference in data source in second column and the one mentioned in fifth column.
Figure 2. What is exclusion criteria for exclusion
What is significance of bibliographic coupling in fight against COVID 19.
What is difference between a literature survey and bibliometric analysis. How it gives a better prospective than a literature survey as mentioned in line 103.
Experimental design: In the methodology section, there is a lot of redundant information. The keywords are already mentioned in abstract why need to present as a separate section. Similarly, article selection and bibiliometric protocols are irrelevant as the review is about COVID-19 not on data mining techniques. The authors if they want should present a simple criteria like selecting only from indexed journals such as PubMed, Google Scholar, MEDLINE, Science Direct, Springer, and Web of Science databases and just mention the search terms.
Also the theoretical literature explaining the ANN ,CNN and LSTM is widely discussed so no need to add mathematical theory .One section about theoretical background that discusses the application of there machine learning algorithms  will be sufficient.
In section 4.1 line 331 what are the classes 4,3, and 2 present?.
Validity of the findings: In section 6 the subsection 6.2 that discusses the trends of publication, bibliometric analysis, authors prolific analysis etc. seems irrelevant. Instead authors should focus on critical analysis of disease itself.
The COVID-19 detection challenges and how authors have dealt them from the presented literature should be discussed as a summary .From the whole presented literature a more precise summary of analysis should be included.
Additional comments: In summary although the authors have prepared a quiet lengthy review article, but there is a lot of information that is not required. As main objective of any survey is to provide readers an up to date literature and a clear comparative picture in terms of results as well as challenges faced and way forward to solve these problems. It is highly recommended to revisit the approach in this paper and follow a simple criteria to present most relevant and useful analysis.


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: EARLY SURVEY WITH BIBLIOMETRIC ANALYSIS ON MACHINE LEARNING APPROACHES IN CONTROLLING COVID-19 OUTBREAKS
Review round: 1
Reviewer: 3

Output:
Basic reporting: In introduction, authors should clearly mention the motivation and address it during the paper. Why is the "bibliometric analysis" important? why authors consider this analysis in this paper.
Experimental design: CNN methods did not describe with details.
Validity of the findings: The conclusion is not satisfactory and cannot convince reader that which methodology is suitable for covid dataset. you should provide that more detailed CNN architecture for each dataset.
Additional comments: 1- Authors should provide more details in Table 3 such as: CNN Architecture, number of patients, and database (e.g. type of preprocessing, name of institute).

2- There are several CNN method for analysing CT and  X-ray scans. Authors must introduce the best architectures in this database or Covid19 case. They only mentioned that CNN methods have a better performance compare to traditional machine learning methods. It is not clear which type of CNNs are suitable for Covid-19.

3- Quality of some Figures are low, Fig.3 and Fig. 14.

4- It is not clear how many cases are used for training and test in Table 3.

5- In conclusion section, I want to read the author's point of view regarding suitable and successful methods in Covid-19 specifically not generally (CNN methods).


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: SHEXML: IMPROVING THE USABILITY OF HETEROGENEOUS DATA MAPPING LANGUAGES FOR FIRST-TIME USERS
Review round: 1
Reviewer: 1

Output:
Basic reporting: Summary:
Based on prior research this paper asserts that proposed domain-specific language (DSL) support is needed in the data transformation among many sources (e.g. JSON and XML) into a RDF output. The paper suggests that there are weaknesses/limitations in the usability of DSLs available currently, and so proposes a new language that allows to transform and integrates data from XML and JSON sources into a single RDF output. An experiment evaluation was conducted alongside an expressiveness comparison among three DSLs (YARRRML, SPARQL Generate and ShExML). The experiment results compares the development time and learning curve metrics as well as the effect on usability of these DSLs. The authors conclude that their DSL is superior on usability aspects to the alternatives and it is going in the right direction.

Pros:
+ Good fit with the scope of the PeerJ Computer Science Journal
+ Topic (data integration and transformation) is of practical and research relevance
+ Good chosen DSLs/languages to evaluate the usability of them for data integration and transformation
+ It was good to see the use of prior studies providing a basis for the features one to one transformations and many to one transformations
+ I liked the intention of authors being rigorous in the experiment reported, in the spite of not adequately formalized and referenced.
+ In general, the paper uses a clear language in terms of the quality of expression

Cons:
- The authors are vague on the make-up of the profile of participants, information that is essential to reader understanding the analysis result
- The threat to validity is not presented
- Precision metric could be better formalized
- Improving the quality and format of the listings
- Improving the quality of the Figures using Tikz and Pgfplots packages, some of them have insufficient resolution (Fig.1 and Fig.2). Besides, use the patterns to fill the sample (lines, dots, dashes, ...) instead of colors in the graphs.
- Some tables and figures are overfull the margin limit

Comments:
* The listenings could be configured to highlight the commands and statements, this is worth to know the syntax and the difference among literals, strings, keywords and so on, in order to improve the usability perception of each language under study.
Structure:
* I missed a Related Work section, mention other works that, somehow, are related to the proposal study
* Results section could be a subsection of Methodology
* I missed a Threat to Validity subsection inside Methodology section

Typos:
- 341: our films example > our example films
- 514: a experiment > an experiment
Experimental design: * I missed a Threat to Validity subsection inside Methodology section.
- Creswell, John W and Creswell, J David. 2017. Research design: qualitative, quantitative, and mixed methods approaches. 2. ed. London: Sage Publications.
* The Methodology section should be better improved, I suggest the following structured:
5 Methodology
5.1 Experiment Protocol
5.2 Conduction
5.3 Analysis Result
5.4 Threat to Validity
* Furthermore, the protocol experiment should be better formalized following a rigorous standard and procedures. See the paper:
- Claes Wohlin, Per Runeson, Martin Hst, Magnus C. Ohlsson, Bjrn Regnell, and Anders Wess ln. 2012. Experimentation in Software Engineering. Springer Publishing Company, Incorporated.
Validity of the findings: * In general, the statistical analysis was very well done, showing excellent results.
* It is a pity that the adherence of the number of experiment participants to the second task (Task 2) was low, making statistical analysis difficult.
* For improvements, I suggest that authors for internal cohesion of responses by applying the Cronbach's Alpha analysis, and mode the responses per respondent and per question.
- Mohsen Tavakol and Reg Dennick. Making Sense of Cronbach’s Alpha. International Journal of Medical Education. 2011; 2:53-55 Editorial.
* Precision could be better formalized. For instance using class agreement of the data labels with the positive labels given by the classifier.
 - Precision: the number of correctly classified positive examples divided by the number of examples labeled by the system as positive:
 - Precision = TP / (TP / FP), where TP: True Positive and FP: False Positive
 - Marina Sokolovaa and Guy Lapalmeb A systematic analysis of performance measures for classification tasks. Information Processing & Management, Volume 45, Issue 4, July 2009, Pages 427-437. https://doi.org/10.1016/j.ipm.2009.03.002
* Again, I claim a Threat to Validity section, describing the internal, external, construct and conclusion validities of the controlled experiment.
Additional comments: To assist the author(s) in revising his/her/their manuscript, please separate your remarks into two sections:
(1) Suggestions which would improve the quality of the paper but are not essential for publication.
See the comments and suggestions described in the 1. Basic reporting, 2. Experimental design and 3. Validity of the findings sections.
(2) Changes which must be made before publication
In general, the article is well written, easy to understand and, in the current format, has merits for acceptance in PeerJ. It is recommended to rewrite the Methodology section, including details about experiment protocol and threat to validity. The Background section presents important concepts and examples of DSLs/languages, but the Related Work is unclear and not discussed in depth with appropriate comparison. In other words, the Related Work section is poor, missing a comparison with other similar studies. Besides, the other sections should be improved, following the detailed comments previously exposed. The main point is that scientific value is perceived by the motivation and the achieved results. Empirical studies, mainly experiments, should be conducted following appropriate protocols for evaluation, which is not the case for the reported experiment, it should be better formalized and referenced.


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: SHEXML: IMPROVING THE USABILITY OF HETEROGENEOUS DATA MAPPING LANGUAGES FOR FIRST-TIME USERS
Review round: 1
Reviewer: 2

Output:
Basic reporting: The (English) language could be improved. I indicatively mention a few cases that need improvement but there are more:
* Data integration is the problem of integrating
* This supposed the creation of a new script
* data integration is performed more easily using ShExML (line 57)
* In the way to offer a simpler solution (137)
* Things like iterators, sources, fields, unions and so on  (391)
* … but they are more or less similar. (392)

Introduction
--------------
The introduction remains too abstract and doesn’t reflect well the reality. For instance, it is mentioned in the introduction that "more recent proposals allow to directly transform multiple data sources into a single representation” (line 47) or “This is an improvement compared to previous techniques as in principle it allows for faster development and improved maintainability.” (line 49-50). However, the claim is not supported by references, not even examples. This occurs throughout the introduction.

It is also mentioned that “ShExML uses Shape Expressions for defining the desired structure of the output. “ (line 53-54) but it is not clarified what Shape Expressions are.

It is also mentioned that “ShExML is intended for users that have some programming background” but later on it is compared with SPARQL-Generate that is intended for users with Linked Data background. In that case, I am not sure if one can compare the two languages.

“We focus on usability of tools based on a DSL” —> I guess we may agree that ShExML or the other languages are DSL but that’s nowhere specified in the text.

2 BACKGROUND
——————————
The main problem I see with this section is that the languages and the implementations are mixed for all cases but it is more evident in the first subsection that is focus on one to one transformations. Given that the paper is focused on languages, I would expect the background section to be similarly focused on language based solutions and be complemented by implementations if they somehow become relevant. For instance, it is mentioned that “Bizer and Seaborne (2004) present a platform to access relational databases as a virtual RDF store. “ but in practice and what is interesting, considering that this paper looks int languages usability, is the D2R language they propose rather than the D2RQ platform they proposed next to the language.

In the same context, it is hard to identify the main trends. For instance, in the case of XML, different solutions are put one next to the other but where did the different DSL solutions were based on? XML Schema, XQuery, XSLT, others? And even more, what were the advantages and disadvantages of these approaches? This way, a reader can better understand what the issues were and we need yet another solution that is inspired from a complete different basis.

In the end of the background section, I am not sure if I know which are the trends of languages and I am not sure why the languages that were chosen for the comparison are representative. At the moment, the comparison against SPARQL-Generate and YARRRML seems to be a random choice which I am sure it is not but this is not clear based on the current version of the background section.

2.1.2 From JSON to RDF
----------------------------
How do you se JSON 1.1 as transformation language for JSON?

2.1.3 From CSV to RDF
---------------------------
I think in this subsection, the notion of CSV and Excel are mixed but when it comes to their transformation to RDF they have quite some differences, so I would recommend to clear this up. One solution would be to distinguish completely the two, the other solution would be to change the subsection’s header to something like “From tables to RDF” and then cover all possible cases of tables. This would, of course, require to consider more than what’s already explored, included databases that are not covered in this subsection.

I think that this subsection does not fully reflect reality overall. CSVW (CSVs), which is DSL based solution but most importantly the only other W3C recommendations for transforming data to RDF, is not mentioned. Besides CSVW, other important contributions, such as Tarql (https://tarql.github.io/) are not mentioned at all. Similar comment goes for the databases section, where significant contributions are not mentioned, such as SML (http://sml.aksw.org/).

2.2.2 Text-based approaches
---------------------------------
I am not confident of the title of this subsection. What is it meant by text-based?

2.2.3 Graphical-based approaches
----------------------------------------
I think that the graphical-based approaches is an example of what I mentioned as my first comment for the background section. If the paper is focused on languages usability, the tools are out of scope in my opinion but the two different concepts (languages and tools) are mixed throughout the paper.
If this authors think that this section is relevant, I would recommend to put it in context and make it more representative. I am sure there are more tools to mention.
Experimental design: 3 PRESENTATION OF THE LANGUAGES UNDER STUDY
------------------------------------------------------------------
Throughout the paper it is mentioned that the three “languages” will be compared but YARRRML is not a language but a YAML based syntax for RML as it is earlier mentioned. So what is going to be compared is the YARRRML syntax of RML with ShExML and SPARQL-Generate. The same claim appears in the abstract “In this work we have conducted a usability experiment on three different languages: ShExML (our own language), YARRRML and SPARQL Generate. “

Then if “YARRRML and ShExML are able to compile their mappings to RML” then we are talking about "syntax sugar” on top of RML language but how SPARQL-Generate becomes comparable? YARRRML could support other languages besides RML, eg SPARQL-Generate, which brings me to my next comment.

It is mentioned in the text that “RML is considered as a lower level middle language to compile” (151) and this is the reason it was not chosen. I would agree that RML might not be the best language for a user to edit but why does this hold for RML and not for SPARQL-Generate? What about the other languages that were proposed and mentioned in the background section? Where do we draw the line and a certain language may be considered lower level middle language?

At the same part, the sentence continues “ (RML is) to be used by programmers and data engineers” (152) but in the introduction it is mentioned that the hypothesis targets “first-time users with some programming background” (56) which confuses me because if the hypothesis focuses on users with programming background then RML should be considered no? I think what it is considered as user for the study should be clarified throughout the whole paper.

I am not sure if it is a good practice to keep such long lists of XML, JSON examples followed by examples in each language. It might be better if they are placed in the appendix but this is more a matter of styling. I would suggest to check what the journal recommends.

I am not sure why “ The originality of ShExML, compared to the other two languages studied here, is that the output is defined only once even when several sources are used.” (384-386) only holds for ShExML and not for the other syntaxes that ShExML is compared with.

3.4 Comparing expressiveness of the languages
--------------------------------------------------------

First of all, it is not explained what is considered in the paper as “expressiveness”. I would suggest to refer to a definition.

My greatest doubt though about this subsection is the list that is used as criteria for expressiveness, e.g., source and output definition, multiple results, transformations etc.
Why are these good criteria? How are we sure that they are complete?
For instance, it is mentioned that “things” like iterators are common in all three languages, their syntax is different but from an expressiveness point of view these features have no differences. (393) However. The KR2RML language for instance (which is not mentioned in the background section) does not require iterators to achieve the same results.

I think this is a very superficial view of what expressiveness might mean in the case of such languages. First of all, their expressiveness is multidimensional. It depends on their expressiveness with respect to the input data, the expressiveness of the language per se and its expressiveness with respect to the output, in this case RDF. On top there are more expressiveness dependencies. For instance, YARRRML’s expressiveness for data transformation depends on FnO’s expressiveness, whereas SPARQL-Generate’s data transformation expressiveness depends on SPARQL. As far as the language’s expressiveness is concerned, SPARQL-Generate’s expressiveness depends on SPARQL whereas YARRRML’s expressiveness depends on RML which, on its own turn, depends on R2RML’s expressiveness. All three languages’ expressiveness depends on their coverage against the RDF specification. For instance, one can generate RDF lists with SPARQL-Generate but cannot do with “core” RML unless the xR2RML extension is considered (xR2RML is also not considered in the background section). Last, the expressiveness of these languages with respect to the input data depends on the formulations they use to refer to them. For instance, if XQuery is considered by one language and XQuery is more expressive than XPath, then the language that considers XQuery to refer to the input data would be more expressive. So, I think that the list of arguments may be considered as possible comparison parameters but I do not think that they can qualify for fully assessing these syntax and languages expressiveness.

Regarding the expressiveness of the ShExML compared to the other languages, how is the expressivity affected by the different formats that are supported? Because ShExML seems to support less data formats.

I think this section would benefit from a comparison table that summarises the differences.

“YARRRML supports named graphs whereas the other two do not.” Are you sure that SPARQL-Generate does not support named graphs?

“in SPARQL Generate it is possible to also transform to text formats, enabling the transformation to a lot of different formats.” (416) I am not sure I understand this

In the end, I don’t understand how we come to the conclusion that SPARQL-Generate has further expressiveness (432-440)

4 FURTHER SHEXML CONSTRUCTIONS
-----------------------------------------------
It is not clear what each feature generates. I would suggest to include more complete examples where not only the ShExML syntax is mentioned but also the expected output

4.1 Nested iterators
----------------------
I am not sure I understand what the purpose is of nested iterators and what is generated if they are used.

5 METHODOLOGY
-----------------------
But based on what we read in the Results section, in the end we have results from 14 students in the first task and only 7 in the second task.
However, in the results results of 17 students are considered even though they didn’t provide complete results. I would suggest to revise.

It is not clarified what the background of the students is. For instance, if the students took classes of ShExML or even ShEx during the semester, it may be explained why they perform faster with ShExML or why they find this easier compared to SPARQL-Generate if SPARQL was not in the course’s curriculum. Statistics regarding the background knowledge of each student should have been recorded before starting the task and provided in the paper.
Validity of the findings: 6 RESULTS
--------------
Given that almost all students but one that filled in the questionnaire for Task 2, only did the task with ShExML, we may only make conclusions for ShExML.
It is not explained what p and ω and H and F. One-way ANOVA, Kruskal-Wallis test and the Gabriel’s criterion are all mentioned but it is not explained why they were chosen and what their parameters prove. For instance, what does it mean that p=0.16 between ShExML and YARRRML and p=0.12 between ShExML and SPARQL-Generate. Why was Gabriel’s criterion used for ShExML and YARRRML and Bonferroni criterion between ShExML and SPARQL-Generate? What about YARRRML and SPARQL-Generate? In the end it is not explicitly explained which syntax is better on what and how the differences are explained.

Why Table 2 has different totals?

For the rest, I am not sure what the number of left and right clicks or mouse scroll and move might indicate. Especially considering if the tool or the language is evaluated.

It is mentioned that "we can see that elapsed seconds has a medium size effect (ω = .60)” (587) but what does this mean?
Additional comments: No additional comments


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: SHEXML: IMPROVING THE USABILITY OF HETEROGENEOUS DATA MAPPING LANGUAGES FOR FIRST-TIME USERS
Review round: 2
Reviewer: 1

Output:
Basic reporting: As far as the background is concerned, I think the authors might not have properly understood my main comment (or I didn’t explain well) with regard to related work. This is even evident in the new subsection that was added (2.3 Related studies). I do not disagree that tools should be mentioned as well if relevant but the languages and tools should not be compared as one and the same. And as long as this holds for the background section, I cannot accept the paper for publishing. I will try to explain the problem with the current text with an example but this is not the only case. That means that the background section should still be reworked to distinguish references to languages and tools and compare only languages with languages and tools with tools. Therefore, the new subsection does not solve the problem. In its current state, apples and oranges are presented and compared as one and the same and this needs to be improved before publishing.

For instance, in the new section it is mentioned “Lefranc¸ois et al. (2017)
tested the performance of SPARQL-Generate in comparison with RML. The results showed that SPARQL-Generate has a better performance when transforming more than 1500 CSV rows in comparison with RML.”

Lefrancois et al. did not test SPARQL-Generate in comparison with RML. Lefrancois et al. compared the SPARQL-Generate implementation which unfortunately happens to have the same name causing confusion with the RMLMapper (not RML). RML is a language and it cannot be compared with a tool. I acknowledge that Lefrancois et al. also phrased it wrongly in the paper but that does not mean we should propagate the wrong phrasing.

The reference to expressiveness definition is not peer reviewed. But more importantly, it does not impact the content of the paper nor explains the features choice. I would suggest to the authors to drop the expressiveness comparison claim and turn it into features comparison or something alike because there is no proof that the chosen features reflect expressiveness. Similarly, the conclusion that SPARQL-Generate is more expressive should be dropped as it is only proven it supports more features but those features do not prove expressiveness.

 I would still like to see a comparison table even if this is a yes/no table and I think this is inline with the other reviewer’s comments.
Experimental design: I’d like to thank the authors for clarifying the background of the students. It is now clear that they had background knowledge directly related to two out the three languages that were compared but not the third one. I would suggest to have this explicitly clarified in the text. Relying on an assumption that the students might have background related to YAML remains an assumption. It should have normally declared the background of students with respect to YAML as it is the case with SPARQL and ShEx.

I would still find useful some explanation of the impact of the results. I did not mean that the statistical measures need to be introduced but an explanation of the results would be beneficial for the paper instead of just reporting numbers.
Validity of the findings: no comment
Additional comments: I would like to thank the authors for their detailed answers overall.

A last comment with regard to easiness of use without expectation of reaction:
The fact that certain languages explicitly claim easiness for use while others not does not mean that the others cannot be easy for use and do not deserve to be compared. For instance, RML was the first language of its kind, we may agree it’s not the easiest to use but when introduced the concept of mapping languages for heterogeneous data sources did not even exist, so of course the language’s purpose at that point was not to prove easiness of use.


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: EFFECTS OF DATA COUNT AND IMAGE SCALING ON DEEP LEARNING TRAINING
Review round: 1
Reviewer: 1

Output:
Basic reporting: This paper investigates some effects of the number of data changes for the feature extraction process in deep learning training. Their investigation is mainly based on the assumption that increasing the image size using interpolation methods would result in effective feature extraction. However, I could not find any arguments in the paper whether this assumption is valid or not. The authors said that if the image data input to the CNN is small, the necessary features may not be extracted. Therefore, they increased the input image data size using the interpolation method. It would be better the authors can give more details for their use of interpolation methods.
I found that the background and problem statement are relevant to enough references.
The paper is well organized and the style of presentation is clearly understandable for the readers.
Experimental design: This paper falls within the scope of the PJ computer and it explains the utilize method in details. However, the method of using deep learning is not much originality. I can give credit for their applications to datasets of small size.
Validity of the findings: This paper highlighted the significant usages of interpolation method for the datasets of small size. Their findings are validated by using medical images.
Additional comments: This paper contains some significant material and method for extracting image features applicable to datasets of small size. It is beneficial for analyzing image data in medicine in which the only a small size of datasets are available.


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: EFFECTS OF DATA COUNT AND IMAGE SCALING ON DEEP LEARNING TRAINING
Review round: 1
Reviewer: 2

Output:
Basic reporting: The goal of the work is to investigate the effects of increasing the image size by using interpolation methods. The authors used a sex classification data set (Gender01) to evaluate their study. The introduction is poor literature supported. The method needs to be extended and explained deeply. The paper is in the scope of PeerJ Computer Science. The nine images in the manuscript are low quality; authors should consider using vector graphic images such as EPS.
Experimental design: Authors have shared the source code of the experimental study through a Jupyter Notebook, which is very useful, however, I respectfully encourage commenting the source code in English to reach a bigger audience. The authors used a suitable experimental setting, and the computational cost was very high.
Validity of the findings: Results corroborated that accuracy was improved by expanding the size using the proposed method.
Additional comments: No additional comments


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: EFFECTS OF DATA COUNT AND IMAGE SCALING ON DEEP LEARNING TRAINING
Review round: 2
Reviewer: 1

Output:
Basic reporting: I have looked at the revised version of the paper.
I did not see any major drawbacks.
So I would like to recommend the paper.
Experimental design: It is good in the revised version
Validity of the findings: It is satisfactory in revised version.
Additional comments: It is an acceptable revised version.


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: EFFECTS OF DATA COUNT AND IMAGE SCALING ON DEEP LEARNING TRAINING
Review round: 2
Reviewer: 2

Output:
Basic reporting: The authors have improved the explanation of the method, as well the manuscript in overall.
Experimental design: The authors included some useful comments in their source code.
Validity of the findings: Results corroborated the conclusions of the work.
Additional comments: No additional comments


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: IMMERSIVE VIRTUAL ENVIRONMENTS AND EMBODIED AGENTS FOR E-LEARNING APPLICATIONS
Review round: 1
Reviewer: 1

Output:
Basic reporting: The use of English is correct. Literature references are enough and the context of the research is well described.

I recommend authors including one or more tables with some results of the study to improve manuscript legibility.

Each of the individual images of Figure 1 should be referenced throughout the text, maybe with a letter (a), (b), ... and properly referenced from the text.

Please, revise the capitalization of reference Sitzmann (2011).

There is a missing white space in Line 190

Should Figures 2, 3, and 4 show bars for the four learning environments?
Experimental design: The research method is described with detail and the manuscript is accompanied by the raw data for replication. The authors have the approval of an Ethics Committee.

The gender was one of the data collected from students, but there is no comment about that in the manuscript.

Please, elaborate on this sentence "existing student satisfaction questionnaires were too broad and inappropriate for this application." (line 224)
Validity of the findings: Conclusions are well stated and speculation is controlled in the text. However, the authors are comparing different VR environments in which the developed humanoid avatar is far from providing a good realistic experience. From my point of view, that is an important threat to the validity of the results.

The virtual experiences are individual whereas the non-virtual ones are in a group with other students. Could this fact affect the results?

The authors used fabricated information to eliminate the possibility of prior knowledge becoming a confounding variable. Could results change whether serious content was used instead? From my point of view, that is a factor authors should be studied for this present research.
Additional comments: I am not very convinced about the utility of the study which analyzes the use of immersive virtual environments for Power-Point based learning. From my point of view, this kind of passive learning doesn't require that virtuality. So, I don't appreciate any potential impact in the paper, but according to the journal guidelines, that is not a concern.


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: IMMERSIVE VIRTUAL ENVIRONMENTS AND EMBODIED AGENTS FOR E-LEARNING APPLICATIONS
Review round: 1
Reviewer: 2

Output:
Basic reporting: The paper presents a study that now more than ever is very relevant. The new COVID situation is forcing universities to quickly shift to virtual learning and thus, it is very interesting to see the study results. (I would also add a paragraph to stress the importance of such practices now in the light of the pandemic).
Experimental design: I am pleased with the experimental design. I only have one question:
Line 177: some participants were paid and some did not. Didn’t this create uneven conditions?
Validity of the findings: With a small size like the one used in the study, normality assumptions are usually not met. In this case, you performed a normality test but I believe you should also use a Kruskal Wallis test. This non-parametric test will provide stricter results and the significance of your findings will be stronger.  I would also suggest to run a Cronbach analysis to test the internal validity of your questionnaire.
Additional comments: This is a very well written work that is also vey relevant due to the current pandemic situation. I have suggested a couple of additions and I believe that the paper will be ready for publication.


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: IMMERSIVE VIRTUAL ENVIRONMENTS AND EMBODIED AGENTS FOR E-LEARNING APPLICATIONS
Review round: 1
Reviewer: 3

Output:
Basic reporting: The paper is clear and self-contained with relevant results to hypothesis set.
The paper is unambiguous, it is well written and it has a good structure.

The authors need to better survey the literature for recent and relevant works on the effectiveness of embodied pedagogical agents and their impact on students learning.

The work also needs a better connection with existing works and authors need to explain how it builds on the findings of related works
Experimental design: The experimental designed is good. I suggest authors to better explain the exact phases of the experimental study. Also the background of the participants need to be discussed in better detail.

The same stands for the results too. Authors need to elaborate and further discuss them.
Validity of the findings: The novelty of the study should be pointed out by the authors in the introduction. Also, the data that was collected via the participants in the experiment and the exact analyses that were performed need to be explained in better detail too.
Additional comments: Authors in this paper address a  very challenging topic that of virtual pedagogical agents and examine their impact on students learning experience and motivation.
The paper is interesting and it has novelty.  In general, I can say that it is well written, it has a good structure.
The introduction could be restructured in order to explain the exact aims of the paper, its highlight out more explicitly the contributions of the work. Also please explain how the present work in could be assistive to the related research community.
The paper is clear and has specific hypotheses that it set. The results are interest. Authors need to address the aforementioned comments in order to improve their work.


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: IMMERSIVE VIRTUAL ENVIRONMENTS AND EMBODIED AGENTS FOR E-LEARNING APPLICATIONS
Review round: 2
Reviewer: 1

Output:
Basic reporting: The authors have properly addressed the posed questions and suggestions.
Experimental design: The authors have properly addressed the posed questions and suggestions.
Validity of the findings: The authors have properly addressed the posed questions and suggestions.
Additional comments: The authors have properly addressed the posed questions and suggestions.


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: IMMERSIVE VIRTUAL ENVIRONMENTS AND EMBODIED AGENTS FOR E-LEARNING APPLICATIONS
Review round: 2
Reviewer: 2

Output:
Basic reporting: The article is well written and easy to follow. The reference list has ben enhanced.
Experimental design: The methodology is adequate and the authors have performed extra statistical analyses, as instructed by the reviewers
Validity of the findings: The statistical methods used provide reliable and valid results, especially in the second version that the authors also used non-parametric approaches.
Additional comments: The paper in now significantly improved and the authors have addressed all reviewer comments. I will suggest publication.


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: APPROACHES COMBINING METHODS OF OPERATIONAL RESEARCH WITH BUSINESS PROCESS MODEL AND NOTATION: A SYSTEMATIC REVIEW
Review round: 1
Reviewer: 1

Output:
Basic reporting: >> Paper title and introduction should be reviewed in relation to “decision making” focus. This focus is not sustained in the other sections of the work.
>> The Introduction does not make it clear that the article is a systematic review and does not discuss the results obtained either.
>> The Introduction lacks a final paragraph describing the structure of the paper.
>> The paper lacks both a Related Work and a Background Section. Regarding Related Work, none of the other systematic reviews on process modeling are cited. Background Section would be useful since many topics like BPMN, Linear Programming, Multicriteria decision making and so on are incorrectly placed in a section named “Methods”.
>> Regarding BPMN, it is not correct do say that “The OMG create this notation…”. This mistake is repeated in page 2 and 3. Furthermore, it is contradictory with other parts of the paper that properly give credit to BPMI.
>> Figure 3 is called on page 5, but it is only presented on page 9. Thus, the figure and the text are very distant from each other.
>> Tables are not ordered. It skips from Table 2 to Table 5 and then back to Tables 3 and 4.
Experimental design: >> The analysis of the distribution of the publications by year is very interesting and the use of BPMN versions as important milestones was important.
>> The analysis of authors  from selected publications are also important, because it helps to discover the community involved with this topic. However, although the table with the results is presented, the authors did not dedicate themselves to analyze these results in detail.
>> In fact, the lack of depth in the analysis is not a characteristic of the authors topic alone. In general, there is a lack of deepening in the discussions of the results found. Therefore, very narrow conclusions were obtained.
>> I do not understand how publications on biological interaction networks (2 papers of Silva and Saraiva) could be included in this systematic review of operational research and BPMN. Considering publications title, it does not look like they are aligned with the systematic review scope.
Validity of the findings: >> “Limitations” does not look like a Section with only 3 lines.
>> The Conclusion does not help to make the contribution of the paper clear. The main findings are poor discussed.
>> The Conclusion lacks a discussion on the opportunity for future work. Therefore, does not identify unresolved questions / gaps / future directions.
Additional comments: Minor comments:
>> The phrase is incomplete in the first paragraph of the Introduction: “Becker et al. (2010)…”
>> The author should review the idea of BPMN as a “graphical writings” (last paragraph of Introduction). It should be more precisely to say that it is a “language”.


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: APPROACHES COMBINING METHODS OF OPERATIONAL RESEARCH WITH BUSINESS PROCESS MODEL AND NOTATION: A SYSTEMATIC REVIEW
Review round: 1
Reviewer: 2

Output:
Basic reporting: The paper provides a systematic literature review of used operational research techniques in Business Process Model and Notation (BPMN) models.

Overall, the paper is well-written and can be considered for publication. I do, however have a few minor comments that need to be addressed before publication:

1)	Please try to make Figure 1 more clear, since the ‘records screened’ and ‘records excluded’ activities fall in between the ‘eligibility’ and ‘screening’ phase. Are these not just screening steps? Or did you put those steps on purpose in between those two phases. If so, please explain in the text why.
Experimental design: 2)	Please explain the criteria for exclusion more clearly, since there are two exclusion activities: ‘records excluded’ and ‘full text articles excluded’. Explain which criteria were used in each of those in the text. It is very important to report this clearly, as the paper is a literature review paper.

3)	The papers that include DMN are rather general and do not really belong to field of operational research. There are, however, papers from the time period that you consider that are more quantitative and more closely related to the topic of the paper. I give the references below, I would like to see them included in the DMN section, or in the “other approaches” section, or in a separate discussion section, as the ones that are included now are not really relevant.

a.	De Smedt, J., Hasić, F., vanden Broucke, S. K., & Vanthienen, J. (2019). Holistic discovery of decision models from process execution data. Knowledge-Based Systems, 183, 104866.

b.	Ghlala, R., Aouina, Z. K., & Said, L. B. (2017). MC-DMN: Meeting MCDM with DMN involving multi-criteria decision-making in business process. In International Conference on Computational Science and Its Applications (pp. 3-16). Springer, Cham.

c.	Hasić, F., De Smedt, J., & Vanthienen, J. (2018). Augmenting processes with decision intelligence: Principles for integrated modelling. Decision Support Systems, 107, 1-12.

d.	Hasić, F., De Smedt, J., Broucke, S. V., & Asensio, E. S. (2019). Decision as a Service (DaaS): A Service-Oriented Architecture Approach for Decisions in Processes. IEEE Transactions on Services Computing.
Validity of the findings: 4)	While the reporting of the results of the literature review is done relatively well, I miss a small discussion section about the implications of the results. What broad conclusions can be drawn from the study? Are there any research gaps / opportunities identified? Some broader findings should be included in a small section before the current limitation section.
Additional comments: No additional comments


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: APPROACHES COMBINING METHODS OF OPERATIONAL RESEARCH WITH BUSINESS PROCESS MODEL AND NOTATION: A SYSTEMATIC REVIEW
Review round: 2
Reviewer: 1

Output:
Basic reporting: >> Related Work Section needs to be deeper developed. Is there any other kind of systematic review on this topic? Why are the authors talking about SOA if it is not related to this paper? There is nothing to say about Operational Research?
>> It seems to me that figures 1, 4, and 5 can have greater legibility, optimizing the use of the space and increasing the size of the letters in texts.
>> I also suggest to include a legend on figures 4 and 5 explaining the numbers in parenthesis, although they are defined in the previous page. Is helps the readers when they are analyzing the image.
Experimental design: >> Keyword Plus by WOS - I did not find any explanation in the text about it. What does “WOS” mean? (all acronyms should be explained). Besides, there is no reference to Keyword Plus. What is the difference to the keywords assigned by the authors method?
Validity of the findings: >> The previous “Limitations” section was removed at all. A section discussing the Threats to Validity is completing missing in the paper.
>> The Conclusion lacks a discussion on the opportunity for future work. Therefore, does not identify unresolved questions / gaps / future directions.
Answer 10: Thanks for the comment, this section has been expanded.
>> Future work analysis is still missing in the new version of the paper.
Additional comments: The main points of the previous review were addressed, and the work has undergone a significant improvement concerning its analyzes.
However, I am still missing a more in-depth related work section and a discussion about Threats to Validity. All works have their limitations, and it is up to the authors to point them out and discuss how they dealt with them in the research.
And as the last point, I would like to suggest again that the work be subjected to an English review, as I identified new errors being introduced in this new version of the work. For instance: “The review business process modelling literature and  describe the…” is a phrase with no meaning.


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: APPROACHES COMBINING METHODS OF OPERATIONAL RESEARCH WITH BUSINESS PROCESS MODEL AND NOTATION: A SYSTEMATIC REVIEW
Review round: 2
Reviewer: 2

Output:
Basic reporting: The paper should be re-read, preferably by an English native, as some sentences are weirdly phrased.

For instance, in the conclusion:
"This area (BE) became one of the papers in 2017, and its significant onset and the future impact can be expected."

Not sure what this sentence means... The BE area became one of the papers... Please rephrase and re-read the entire paper to make it ready for publication.
Experimental design: I have no remaining comments regarding study design.
Validity of the findings: While my previous comment on validity of findings was partially addressed, I still expect a deeper discussion on research gaps and future opportunities, specifically in combining BPMN and operational research. Open topics for future research should be identified more clearly.
Additional comments: No additional comments


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: APPROACHES COMBINING METHODS OF OPERATIONAL RESEARCH WITH BUSINESS PROCESS MODEL AND NOTATION: A SYSTEMATIC REVIEW
Review round: 3
Reviewer: 1

Output:
Basic reporting: I have no remaining comments. The authors addressed my observations.
Experimental design: I have no remaining comments. The authors addressed my observations.
Validity of the findings: I have no remaining comments. The authors addressed my observations.
Additional comments: I have no remaining comments. The authors addressed my observations.


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: APPROACHES COMBINING METHODS OF OPERATIONAL RESEARCH WITH BUSINESS PROCESS MODEL AND NOTATION: A SYSTEMATIC REVIEW
Review round: 3
Reviewer: 2

Output:
Basic reporting: I suggest that the paper undergoes thorough English proof-reading before publication.
Experimental design: No further comments.
Validity of the findings: No further comments.
Additional comments: No further comments.


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: 4D STREET VIEW: A VIDEO-BASED VISUALIZATION METHOD
Review round: 1
Reviewer: 1

Output:
Basic reporting: This paper proposed a new visualization scheme named “4D Street View". In general, this paper is well organized and explains the new method comprehensively.
Experimental design: The analysis of the huge simulation data is a well-known problem. I agree that the new technology presented in this paper contributes to improving this difficulty. The concept of the 4D street view, which enables walkthrough inside huge omnidirectional movie files, is new. The paper presents the details of their implementation sufficiently.
Validity of the findings: The following points potentially fail to meet the requirement of this journal.

(i)	Frequently, the author argues the smoothness of changing videos or operations as the advantages of their video management without showing objective data. Thus, it sounds subjective to me, a bit. To improve the presentation I suggest adding the video of operating the 4D street view application, or measured latency time for changing the views.

(ii)	The sample problem of voltex simulation seems to be not suitable to demonstrate the impact of 4D street view, because the iso-surface and glyphs in Fig. 10 to 13 are too simple. The postprocessing visualization with such as Paraview and geometry files may utilize such visualization more flexibly.

(iii)	As for (ii), the author may claim the large data size of raw data in line 414 in comparison to the data size of videos for 4D street view. However, some recent community software support to output not only the raw data but also the geometry (polygon) data. Then we can analyze the output geometry files in the post process visualization in a more flexible way than 4D street view. Thus, for fairness, the data size of movies and polygon data should be compared to justify the proposed scheme. Since the data size of the geometry increases with the complexity of objects, it was difficult to see why 4D street view is useful with the simple geometry objects in the demonstration.

(iv)	Data size comparison around line 414 should be involved in the discussion or result section, not in conclusion.
Additional comments: No additional comments


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: 4D STREET VIEW: A VIDEO-BASED VISUALIZATION METHOD
Review round: 1
Reviewer: 2

Output:
Basic reporting: The language of the paper is clear and easy to understand for a specialist. I have found a small mistakes in the text, like a missing numbers in the references to Sections. so I recommend authors to check the text before publication.
The graphical data is clear and of good quality.
Experimental design: The research is within the scope of the journal. The main topic is in the field of scientific visualization and computer graphics.

The paper does not describe experimental research, so nothing can be said about the experiment design. The example chosen by authors to show the performance of the method is simple, but it shows the results.
Validity of the findings: The proposed solution is relevant to any fields of science and engineering where there is a need for 3D simulations of physical fields. It may be easily applicable to other areas of human activity - virtual tourism, education etc.
Additional comments: The paper presents a method of scientific simulation data visualization. Authors developed a method for visualisation of the 3D simulation results, which may find an application in the fields like fluid mechanics, atmospheric and ocean science, or any other were there is a need to visualize a complex 3D fields of physical quantities. One of the main contributions of the proposed method is an application of omnidirectional cameras for visualization which replaced the standard projective model. Another important impact is a development of a tool for post-visualization. In the new approach, when a user wishes to change the viewing angle while looking at the graphics, the new view is not recomputed, but downloaded as a frame from a precomputed set of video data. This approach will surely speed up the process of an analysis. However, there are issues which should be addressed.
1) Clearly the approach would benefit any post-simulation analysis of results. But a question is what is the storage space needed for a set of precomputed videos compared to the space needed for raw 3D visualization data? Its important in the case of high-resolution video and small steps of simulation.
2) Authors mentioned a use of compression of video data in the set. But this approach leads to the lose of information since small changes may be lost after the compression is applied. Can authors comment on this?
3) If the video set is predefined at the time of the simulation how one can smoothly change the views while looking at results? There will be jumps visible to a user. For simpler scenes it won't be an issue if one uses traditional real-time computer graphics. Can you considered some kind of blending of views when the number of cameras per volume is not enough to provide smooth transition between views?


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: 4D STREET VIEW: A VIDEO-BASED VISUALIZATION METHOD
Review round: 2
Reviewer: 1

Output:
Basic reporting: The revised manuscript properly responded to reviewer comments.
Experimental design: no comment
Validity of the findings: no comment
Additional comments: No additional comments


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: 4D STREET VIEW: A VIDEO-BASED VISUALIZATION METHOD
Review round: 2
Reviewer: 2

Output:
Basic reporting: The revised version of the manuscript contains answers to the reviewer's questions asked in the previous review report. Therefore, I think that the paper is suitable to be published in the journal. Also, the overall structure of the article has been improved. New simulations and provided graphics give an additional insight in the presented topic.
Experimental design: The new version of the manuscript shows an importance of the proposed method for the scientific visualisation of the simulation results. Three topics has been covered: thermal convection in spherical shell, magnetohydrodynamics turbulence phenomena and vortex ring formation.  Topics are well chosen to present the benefits of the new visualisation method - the included graphics shows .
Validity of the findings: I think the choice of magnetohydrodynamics simulation for an assessment of the proposed visualisation method is correct. The included graphics shows the complexity of the phenomena which can be better understood is one has a possibility of the view manipulation of the proposed visualisation tool.
Additional comments: The revised version of the manuscript contains answers to the reviewer's questions asked in the previous review report. Therefore, I think that the paper is suitable to be published in the journal. Also, the overall structure of the article has been improved. Provided graphics with results of simulations gives additional insight in the presented topic.


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: STOCHASTIC COMPUTING IN CONVOLUTIONAL NEURAL NETWORK IMPLEMENTATION: A REVIEW
Review round: 1
Reviewer: 1

Output:
Basic reporting: The article must be written in English and must use clear, unambiguous, technically correct text. The article must conform to professional standards of courtesy and expression.
Experimental design: The investigation must have been conducted rigorously and to a high technical standard. The research must have been conducted in conformity with the prevailing ethical standards in the field.
Validity of the findings: The conclusions should be appropriately stated, should be connected to the original question investigated, and should be limited to those supported by the results. In particular, claims of a causative relationship should be supported by a well-controlled experimental intervention. Correlation is not causation.
Additional comments: This paper is totally well written easy to understand because the authors did a good conclusion on the part of basic concepts. This manuscript mainly researches several questions such as developments of SC CNN and how does it compute etc. Thus, authors must be concerned about some details as follows:
1. I suggest the authors attach all the figures and place them around the appropriate paragraph respectively in the manuscript as much as possible. Anyway, authors must improve the quality for all the figures, font size must be adjusted and unified, the resolution must be improved. If all the figures are quoting, authors must indicate references respectively.
2. This manuscript has too many abbreviations and parameters. Therefore, if necessary, I suggest authors should list a nomenclature table with its name, unit of measurement, and description of all variables (explanation) at the beginning of this manuscript.
3. In the Basic Concepts section, some algorithms and methods such as logical formulas should be more concise. Some expressions should be modified to the mathematical mode when using exponential computing, for instance, 2n, instead of 2^n.
4. Related work is not enough in this paper, authors should quote the latest references (2019-2020). In addition, this manuscript is weak in part of the conclusion. It will be better if authors make a summary and extension for each research work in "SC implementation in CNN's".
5. What are the development prospects of the SC CNN algorithm? And how did other relevant researchers prepare to process the open problems? By the way, the author's personal views throughout this paper are quite weak, this section must be restructured and polished.
6. Because of the development of CNN architectures, various models based on CNN such as ImageNet and googLeNet etc. Authors need to compare the performance variation between state-of-the-art CNN architectures and traditional CNN during SC Implementation.


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: STOCHASTIC COMPUTING IN CONVOLUTIONAL NEURAL NETWORK IMPLEMENTATION: A REVIEW
Review round: 1
Reviewer: 2

Output:
Basic reporting: This submission reviews the key concepts of Stochastic computing (SC) and the circuit structure and then compare the advantages and disadvantages amongst different methods. Finally, This submission concludes the overview of SC in CNN and make suggestions
for widespread implementation in the near future.
Experimental design: This submission is within the scope of the journal
Validity of the findings: This is a review without technical novelty.
Additional comments: This submission is with good discussions.


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: STOCHASTIC COMPUTING IN CONVOLUTIONAL NEURAL NETWORK IMPLEMENTATION: A REVIEW
Review round: 1
Reviewer: 3

Output:
Basic reporting: English writing should be improved in this manuscript.
Experimental design: no comment.
Validity of the findings: no comment.
Additional comments: This review article introduces stochastic computing and deep learning, especially CNN based SC methods. This is quite helpful for these researchers in this field.

1, English writing should be improved. Some statistical results should be shown in tables instead of sentences.
2, More recent researches should be introduced for better description.


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: STOCHASTIC COMPUTING IN CONVOLUTIONAL NEURAL NETWORK IMPLEMENTATION: A REVIEW
Review round: 2
Reviewer: 1

Output:
Basic reporting: No comment.
Experimental design: No comment.
Validity of the findings: No comment.
Additional comments: No additional comments


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: AUTOMATIC MODULAR DESIGN OF ROBOT SWARMS USING BEHAVIOR TREES AS A CONTROL ARCHITECTURE
Review round: 1
Reviewer: 1

Output:
Basic reporting: This paper concerns the automatic design of controllers for swarm robotics. Building on the AutoMoDe work of Francesca et al, they extend the methodology to encompass the use of behaviour trees as a control architecture. They evaluate the new method, termed Maple, against the Chocolate AutoMoDe variant, and against a neuroevolutionary approach termed Evostick. The evaluation is performed on two classical swarm tasks, aggregation and foraging. They show that, like Chocolate, and unlike Evostick, the new method successfully crosses the reality gap. The paper is generally well written and structured, with good supporting references. Results are presented clearly, and data and code is shared.
Experimental design: The Maple algorithm builds on previous work and reuses a set of basic low-level behaviours and conditions, which corresponded to state machine states and transitions in that work. These behaviours (actions) and conditions are placed as leaf nodes in a restricted behaviour tree structure, consisting of up to four branches, each with exactly two leaf nodes. Iterated F-race is used to optimise the contents of the leaf nodes within this fixed structure. Candidates are evaluated in simulation during the optimisation. Three studies are performed, in each case using two tasks, foraging and aggregation. Study 1 looks at performance in simulation and in reality, hypothesising that the modular nature of Maple should result in similar reality gap crossing behaviour to Chocolate.  This is demonstrated with nice results clearly showing the similar advantages of Maple and Chocolate over Evostick. Study 2 compares the performance of Maple and Chocolate at different simulation budgets for optimisation, hypothesising that Maple should converge on high performing solutions faster than Chocolate, since the search space is smaller. This is shown to hold when the simulation budget is small, but Chocolate performs better at higher simulation budgets.

Study 3 looks at the effect of variations of the behaviour tree structure and compares them to the previous Maple results. This section is perhaps overlong, with many variants described then discarded, and the results could be summarised in a boxplot for more clarity. There are interesting hints here about the limits to the Iterated F-race optimiser.
Validity of the findings: I am perfectly happy with the validity of the results.
Additional comments: In Study 1 (line 411) the authors speculate about the cause of the reality gap performance loss with a rather unevidenced assertion about robots unable to move due to frictions. Please can you elaborate on this.

In Study 2, I would like to see some more discussion about the reduced complexity of available solutions limiting ultimate performance of Maple compared to Chocolate.

In Study 3, please shorten the discussion of variants, particularly the uninteresting ones, and summarise comparative results with boxplots.

The argument is advanced that these low-level behaviours have no natural termination criteria and thus do not fit into the standard behaviour tree methodology whereby a node can return success, failure, or running, and can only return running. This is partly used to justify a restricted behaviour tree structure. I think this is not quite correct. The motors could be regarded as contested resource that only a single action node could access in a control step. The first action node to actuate the motors could return a ‘success’, all other action nodes within that control step that are also ticked could not access the motors and would return ‘running’, indicating an uncompleted action. This would allow a more general behaviour tree structure.  Perhaps this could be reflected in the future work.

Future work could also expand on possibilities for developing the optimisation algorithm, this is already hinted at.

Minor error: line 103 typo, should be ‘planning’

Overall, I enjoyed this paper and think it is a solid contribution to the field.


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: AUTOMATIC MODULAR DESIGN OF ROBOT SWARMS USING BEHAVIOR TREES AS A CONTROL ARCHITECTURE
Review round: 1
Reviewer: 2

Output:
Basic reporting: The manuscript presents an automatic modular design of robot swarms using behavior trees as a control architecture. Using behavior trees in swarm robotics is a challenging topic. It is possible to find different approaches in literature as well. It is a popular topic for robotics researchers.
The paper is a well-written paper and language is clear.
The abstract should be more specific and deal with the novelties and contribution of this study, strongly.
The authors must emphasize differences between the manuscript and their previous work strongly.
It is necessary to do a new literature review. The introduction part of the manuscript must be revised. The authors should improve the introduction part according to a new literature review.
Figures and tables are good enough.
Experimental design: Manuscript's title and abstract are the same with supplementary files of the authors' previous work which was published at the ANTS 2018 conference in 2018. The necessary links are listed below. The authors must emphasize differences between the manuscript and their previous work strongly. And, in my opinion, they must change the abstract and title of the manuscript.

- The abstract should be more specific and deal with the novelties and contribution of this study, strongly.  And authors must emphasize differences between the manuscript and their previous work strongly.
- Experimental studies are good enough.
- The manuscript contains significant outcomes.
Validity of the findings: - Experimental studies are good enough.
- The manuscript contains significant outcomes.
Additional comments: First of all, I would like to thank for authors' valuable work. The manuscript presents an automatic modular design of robot swarms using behavior trees as a control architecture. Using behavior trees in swarm robotics is a challenging topic. It is possible to find different approaches in literature as well. It is a popular topic for robotics researchers. The paper is a well-written paper and its topic is important. I have a few suggestions to authors which are listed below.

- The abstract should be more specific and deal with the novelties and contribution of this study, strongly.  And authors must emphasize differences between the manuscript and their previous work strongly.
- It is necessary to do a new literature review. The introduction part of the manuscript must be revised. The authors should improve the introduction part according to a new literature review.


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: AUTOMATIC MODULAR DESIGN OF ROBOT SWARMS USING BEHAVIOR TREES AS A CONTROL ARCHITECTURE
Review round: 2
Reviewer: 1

Output:
Basic reporting: No comment
Experimental design: No comment
Validity of the findings: No comment
Additional comments: I am happy that the authors have addressed the points raised in my previous review.


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: REAL-TIME QUINTIC HERMITE INTERPOLATION FOR ROBOT TRAJECTORY EXECUTION
Review round: 1
Reviewer: 1

Output:
Basic reporting: This paper is well-written. The number of references is relatively small.
Experimental design: The authors only consider one joint to perform experiment. In future, three or more joints are suggested to consider, since it would have more strict requirements on real-time。
Validity of the findings: The experimental results demonstrated that real-time motion application from Python is possible.
Additional comments: This paper investigates a real-time joint trajectory interpolation system for the purpose of frequency scaling the low cycle time of a robot controller. A re-connectable real-time motion service is established. And the experimental results demonstrate that real-time motion application from Python is possible.  This paper is well-written. And the following comments could be considered.

1. In  Introduction, it is suggested to add some statements about contributions of this paper.

2. It is suggested to add some related references.

3. This paper only considers one joint to perform experiments. In future,  a robot with three or more joints is suggested to consider, since it would have more strict requirements on real-time。


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: REAL-TIME QUINTIC HERMITE INTERPOLATION FOR ROBOT TRAJECTORY EXECUTION
Review round: 1
Reviewer: 2

Output:
Basic reporting: a.	A central term in the article is Real-time. The author should more clearly distinguish between when he is talking about Computer Science Real-time (a deterministic execution period with no relation to latency) and a, in lack of a better expression, “linguistic” real-time (the notion of events happening “right now” with no/low latency)
b.	I wonder if the results of Lind et al. from 2012 still holds with respect to arguing that Python is inadequate in calculating kinematics fast enough on a contemporary computer.
c.	The claim at line 62-64 that Numpy and SciPy is a magnitude slower than C++ is unsupported. As both Python packages are implemented in C I doubt if this holds.
d.	I am missing a discussion regarding the choice of interpolation method. Why use Hermite interpolation instead of I.e. regular Newtonian interpolation. No reference to other papers using Hermite interpolation is mentioned in the introduction. Is it a novel idea or a commonly used method for joint trajectory interpolation?
e.	I generally think more effort should be put into explaining the chosen interpolation method to make it more of a stand-alone work and to make it easier to follow along.

Typos/ grammar:
Fig 1b: The newly calculated mic-pose should be returned to from Updater to Responder.
Proof read lines 103, 125, 150
Experimental design: a.	Why is a cosine motion chosen, when only a (almost) linear path of the trajectory is shown?
b.	Why not use a TCP connection to the controller instead of UDP (mentioned at line 108) to avoid the “blackouts” described at line 191. The first line of the discussion states that these blackouts are currently the biggest challenge, but TCP should ensure that all packages are received.
c.	Why is the absolute acceleration values shown in figure 3a different from those in figure 3b when the author at line 199 states that it is the same trajectory?
d.	Is the position error fed back to the Motion Service?
i.	If yes, how is the tracking actually performing compared to the commanded trajectory shown in figure 5a?
ii.	If not, how is the cutting action relevant for the contributions of the article?
Validity of the findings: No comment
Additional comments: Generally a sound work. The chosen cutting application and sudden shift of focus from trajectory tracking to force estimation is a bit confusing.


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: REAL-TIME QUINTIC HERMITE INTERPOLATION FOR ROBOT TRAJECTORY EXECUTION
Review round: 2
Reviewer: 1

Output:
Basic reporting: No comment
Experimental design: No comment
Validity of the findings: No comment
Additional comments: The version of the paper can be accepted.


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: REAL-TIME QUINTIC HERMITE INTERPOLATION FOR ROBOT TRAJECTORY EXECUTION
Review round: 2
Reviewer: 2

Output:
Basic reporting: no comment
Experimental design: no comment
Validity of the findings: no comment
Additional comments: After reviewing the changes and the author's rebuttal letter, I have no further comments or suggestions for improvements


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: A MULTI-TASK PIPELINE WITH SPECIALIZED STREAMS FOR CLASSIFICATION AND SEGMENTATION OF INFECTION MANIFESTATIONS IN COVID-19 SCANS
Review round: 1
Reviewer: 1

Output:
Basic reporting: The goal of the work is to proposes a multi-task pipeline that takes advantage of the growing advances in deep neural network models. The authors used Inception-v3 and transfer learning, as well as widely adopted datasets. The paper is in the scope of PeerJ Computer Science. The introduction is extensive literature supported. Some grammatical errors are there in the content, need to be removed. Some images are low quality, such as Figure 1, 4, 5, 6, 7, 8, 9; authors should consider using vector graphic images such as EPS.
Experimental design: A big computational effort was made. The authors evaluated the segmentation proposal using COVID-19 CT Segmentation Dataset, which is suitable.

Random transformations such as rotation, horizontal and vertical translations, zooming and shearing, were applied to increase the training data. However, there is a big concern regarding data augmentation. The authors should describe in detail in their work how was data-augmentation applied, e.g. how many images were increased in each category? Was data augmentation used in train, validation and test? The above can affects the results if augmented images from training were used in validation or test.

Apparently, the authors used hold-out for training and testing respectively, however, this is one of the simplest evaluation methods considering the low number of available images; there are other more exhaustive evaluation methods such as k-fold cross validation and leave-one-out cross validation which are more appropriate in this context.
Validity of the findings: The authors should support the Conclusions based on the performance in the test data, in this regard, the experimental study needs to be clarified in order to sustain the validity of the work.
Additional comments: No additional comments


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: A MULTI-TASK PIPELINE WITH SPECIALIZED STREAMS FOR CLASSIFICATION AND SEGMENTATION OF INFECTION MANIFESTATIONS IN COVID-19 SCANS
Review round: 1
Reviewer: 2

Output:
Basic reporting: The present work proposes COVID19 detection and CT scan segmentation method using deep learning model for. The field is important, and the use of deep learning can help for quick diagnostic for COVID19 diagnostics.
Experimental design: The following comment can enhance the work:
1-	Many methods use transfer learning for detection. The authors should give a simple comparison with the existing methods.
2-	A table that summarize the hyperparameters and some details about the proposed segmentation model.
3-	It better to move section dataset to be after the proposed method or as subsection of experiments section.
4-	There are few methods for COVID19 lung infection segmentation. the authors should add these methods in comparisons including [1].

[1]   Elharrouss, O., Subramanian, N. and Al-Maadeed, S., 2020. An encoder-decoder-based method for COVID-19 lung infection segmentation. arXiv preprint arXiv:2007.00861.
Validity of the findings: 5-	The quality of some figures should be enhanced. Like figure 8.
Additional comments: No additional comments


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: A MULTI-TASK PIPELINE WITH SPECIALIZED STREAMS FOR CLASSIFICATION AND SEGMENTATION OF INFECTION MANIFESTATIONS IN COVID-19 SCANS
Review round: 2
Reviewer: 1

Output:
Basic reporting: The authors have added and clarified questions from previous revision. The introduction and methods are well literature supported. There are some grammatical errors in the manuscript, e.g. lines 242-246.
Experimental design: The authors used several evaluation metrics, some of them specially applied for imbalance data, which was suitable. In lines 324-329 the authors stated that the proposal was evaluated by using the following setting: Task 1 5000 for training and 403 for testing, Task 2 9618 for training and 955 for testing, Task 3 5219 for training and 536 for testing. Could you briefly clarify in this section of the manuscript how many times did you repeat this evaluation? For example, you evaluated Task 1 with 5 repetitions, choosing a set of 955 different images in each of them for testing, and 9618 for training. The header of Table 4 seems to give this information; however, it is expected full setting is explained in the section already mentioned.
Validity of the findings: Results corroborated the proposal outperformed other state-of-the-art techniques.
Additional comments: No additional comments


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: A MULTI-TASK PIPELINE WITH SPECIALIZED STREAMS FOR CLASSIFICATION AND SEGMENTATION OF INFECTION MANIFESTATIONS IN COVID-19 SCANS
Review round: 2
Reviewer: 2

Output:
Basic reporting: the authors respond to my comments
Experimental design: the presentation has been reviewed and the authors respond to my comments.
Validity of the findings: --
Additional comments: --


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: TOWARDS FAIR PROTOCOLS AND WORKFLOWS: THE OPENPREDICT USE CASE
Review round: 1
Reviewer: 1

Output:
Basic reporting: Celebi, Moreira and colleagues report on their experience trying to represent and reproduce the results of a highly cited workflow (PREDICT) and share their learnings when applying the FAIR principles to workflow objects. The authors provide extensive background information on the state of the art and propose a semantic profile for representing essential information and making workflows FAIR. The semantic profile constructed by the authors builds on top of several well established frameworks, thus following best practice by reusing existing model when available and suggested extensions where applicable.
The work is extensive however the major comment on the manuscript is its length. We feel that the key message is diluted in extensive textual narrative. It may therefore be beneficial from changes to slimline some of sections.

clarity and style sometimes gets in the way, for example at line 215: "the data scientists highlighted the need of defining a generic way of computational and  manual workflows," -> please check the english or rephrase.

another example: line 630 "Responding competency questions" -> "answering" should be used instead of 'responding'
" Besides evaluating whether each FAIR principle was addressed, we also assessed the profile ontology using the common semantic validation approach, which is based on SPARQL queries used to respond  the competency questions.

again s/respond/aswer/ and is it 'profile ontology' or 'ontology profile' ?

In the Abstract, but also in the introduce, could the authors clarify what they mean by 'dynamic workflows' (abstract and at line 190).
Experimental design: The purpose and aim of the study (a case study) are clearly outlined.
Starting from an assessment of the PREDICT workflow, identifying the necessary steps to make a workflow FAIR, from clarifying input data and building a semantic profile to make the workflow 'self-explanatory' and self-describing.
Validity of the findings: The authors present the difficulties faced when attempting to reproduce and execute the PREDICT workflow. They highlight the difficulties of reusing existing semantic workflows, the problems of domain specific semantic and ambiguity in mapping across.

In the introduction, at line 193, the authors indicate having identified 'disturbing issues'. What are those?
If the authors have reached out to the original authors of PREDICT, it would worth highlighting that fact and possibly document the reasons supplied by the authors for not supplying the original data in the first place.

Table 1 should be introduced much earlier (i.e. under the 'FAIRified Data Collection' section). It would be make it clear for the readership that the original data is not available (please confirm). Table 1 should also be expanded to include last acmes dates, release points for PREDICT, openPredict v1 and v2.
Additional comments: A nice manuscript with rich information, interesting topic and insights but somehow undermined by overwhelming background information. I would suggest a leaner write up, more concise with making the path from PREDICT to OpenPredict more clear to the readership, possibly adding a figure highlight the various steps, (e.g. obtention of input data, ETL, building semantic profile and creation of instances.

Below are a number of suggestions and things I have caught.

introduction
-----------

minor:
	line 44: "The emergence of public data, fueled by a combination of literature curated knowledge and ‘omics data, that has created exciting opportunities for computational drug repositioning."
	 drop "that" in the sentence.
	 suggestion: replace 'emergence' with 'availability'
	 suggestion: replace 'fueled by', with 'either in the form of literature curated knowledge or omics data....""

	 line 68: "The main contributions of this paper therefore are (a) general guidelines..."
	 suggestion: "Therefore, the main contributions of this paper are (a) general guidelines..."

BACKGROUND
Reproducibility of scientific workflows
------------------------------------------

(QR1) What are the input and output variables of an experiment (overlaps with QW2 and QW3);

Could the authors clarify the meaning of 'experiment' in such context ? Also what do they mean by 'variables' associated to an experiment?

The FAIR ecosystem:
------------------
line 168:
"For example, to represent the dataset about protein-protein interactions in human interactome (a CSV file), Bioportal provides the “protein-protein interaction” class."

Can the author be more specific here ? my personal query over bioportal retrieves 23 hits, one of which corresponds to a deprecated class.
It would be nice if the authors could explain which ontology ressource

line 176: (minor comment)
there should be a break and a new section created. "The FAIR principles have received significant attention, but little is known about how scientific protocols and  workflows can be aligned with these principles."

line 180: what are "big data-type applications" ?

line 187: unclear sentenece: "For example, it guides the re-use well-maintained libraries packages rather than reimplementing;" - please rephrase

line 191: "This is important because the details of a scientific workflow with the different steps and parameters are often imprecisely  detailed in scientific publications and therefore cannot be reliably reproduced." This sentence should be backed by evidence or a citation.

line 207:
"The main goal of these short interviews was to align some characteristics required for the FAIR workbench (that rely on our ontology) with the needs of  the researchers, especially from the drug discovery and repurposing domains."

The auhors may wish to introduce the notion of FAIR workbench, as it is not defined anywhere.  Also, the sentence may benefit from swapping the clauses around, ie:

The main goal of these short interviews was to align the needs of  the researchers, especially from the drug discovery and repurposing domains, with some characteristics required for the FAIR workbench , a tool which....and that rely on our ontology".

line 215: "the data scientists highlighted the need of defining a generic way of computational and  manual workflows," -> please check the english or rephrase.

line 218: "A unanimous recommendation is to allow the separation of the workflow steps from  the workflow hyper-parameters, so that one can run the same workflow many times without changing the workflow itself."

This sentence lacks clarify. The readers should be reminded of what 'hyper-parameters' in the context of machine learning.

The authors should define what a workflow step is and how they differ from a workflow or an instruction.
also, it would be important to give the differentiating properties of a 'manual step' and a 'computational step'

some of the definitions come later in the text but the current organization of the manuscript makes reading hard at times.

Distinguishing between A workflow specification and a workflow execution and local parametrisation (paramter setting for a workflow run)

 I have some issues with the following sentence:
 Line 282: "It is often the case that a data scientist needs to manually execute computational instructions, a capability that some workflow systems have, such as Jupyter Notebook (execution of instructions cell by cell)."

I am a bit inconfortable calling Jupyter Notebook a workflow system. While it has some features of a workflow execution system, it is according to its description  " an open-source web application that allows you to create and share documents that contain live code, equations, visualizations and narrative text. "
Furthermore, Jupyter notebook are very sensitive to cell state and order of execution.
But again, i come back to the issue of providing a clear example of a 'manual step', which can not be subsumed into a "computational one".

line 297: "our approach is leveraged by the best practices on reusing parts of semantic models to build a profile ontology." -> rephrase: what about "our approach follows the best practices, promoting ontology and semantic model reuse to build an ontology profile"

Figure 1:
What kind of representation formalism is used ? it seems ER diagram with UML features but this should be stated as well as the software used to create the figure.

Figure 2:
Poor resolution with blurring and low quality (but this is only true for the figure embedded in the pdf document for review, the originals seem of high enough quality, feel free to disregard the comment)

Line 405: typo: opmw:WorkflowExecutionArtifcat -? opmw:WorkflowExecutionArtifact

Line 435: FAIRified Data Collection

PREDICT was published in 2011 by Gottlieb et al:
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3159979/

when the authors list the sources of data, it is actually unclear which exact version is actually used. Could the authors clarify that point by providing a release point or a link to the actual source file or endpoint hit for data download?

for instance, HPO provides its annotation files from http://compbio.charite.de/jenkins/job/hpo.annotations.monthly/lastStableBuild/

Could the authors provide a table listing the exact version and build of the source files they have used for that work ?

line 449: "449 The data that are not in linked data format (RDF) were converted to RDF with a FAIRification process Jacobsen et al. (2019)."

Can the authors provide the full list of such data?
The FAIRification process isn't really described for such sources. Jacobsen et al indicate that a semantic model needs to be build. Where are those for such data sources?

the table should be referenced much earlier, making reading much easier and sending a clearer message.

Table 1. All datasets used in OpenPREDICT version v0.2

however this table should be augmented to include the actual dataset versions (and release dates) used in the initial PREDICT paper in order to highlight the differences between PREDICT and OPENPREDICT datasets.

line 666: "OpenPREDICT v0.2 computational steps use more 2 datasets:"  -> should be  "OpenPREDICT v0.2 computational steps use 2 more datasets:"

Discussion Section:

Major comment:
"Our study was unable to fully reproduce the dataset and accuracy of the method reported in the PREDICT paper."

The main difficulty I ran into when going over the manuscript is understanding which input datasets have been actually used in this reproduce exercice. From that statement, I would assume that Table 1 should collate all the datasets *actually* used in the paper by Gottlieb et al, but that is not the case.

Table 1 therefore holds a list of datasets released after the Gottlieb paper and therefore represent a very different input. There should be not surprise being unable to reproduce the same

Minor comment: English is sometimes an issue hurting the flow, so I would encourage another round of proof reading.
e.g. "During reproducing the PREDICT study, we faced the following challenges" -> "While attempting to reproduce the PREDICT study, we faced the following challenges"

Reproducibility Challenges:

Acknowledgement:
 April fool?