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: SHOULD I USE FIXED EFFECTS OR RANDOM EFFECTS WHEN I HAVE FEWER THAN FIVE LEVELS OF A GROUPING FACTOR IN A MIXED-EFFECTS MODEL?
Review round: 1
Reviewer: 3

Output:
Basic reporting: The manuscript focuses on the use of Mixed-effects models in ecology, specifically their use to account for non-independent observations due to grouping of e.g. sites. It is well written, in a way that is very accessible to most ecologists. The author focuses on the “5-level” rule, where researchers have a strong focus on the number of levels required to estimate the variance parameter(s) of a random-effect. Specifically, the author focuses on the case of a random intercept, with a balanced designed and two predictors. Though Generalized Linear Mixed-models are mentioned on various places, the manuscript only focuses on (General) Linear Models (LMs) and Linear mixed-effects models (LMMs). The manuscript could be significantly improved by expanding the simulations to include GLMMs, though I understand that requires significantly more work. Alternatively, the author can keep focus on LMMs, but then please remove the references to GLMMs entirely, as results are likely to differ depending on the chosen distribution.

Unfortunately, the text includes a range of strong, and/or subjective, statements without references, that needs to be tempered. This strong language use is unnecessarily off-putting, and makes it harder to convince a reader of the, in my opinion, valid argument of treating a rule-of-thumb as a rule instead (in addition to it being mildly annoying).

The figure legends should be revised, to only include an explanation of a figure, rather than including results and/or discussion of those results.
Experimental design: The author fits linear mixed-effects model, and retrieves p-values, to explore if misspecification of the model (i.e. no random-effect when it is required), increases Type-I error. However, in various places in the manuscript (e.g. line 281 and figure 4) the author misinterprets the p-value as (for example) “probability of the null hypothesis”. A p-value is always accompanied by a test-statistic,  though the author does not state anywhere in the manuscript which test is used (in the lmerTest R-package), so that the paper focuses on p-values, rather than on the test that the p-value is a result of. This is a mistake many ecologists make: please correct this throughout the manuscript. Additionally, note that a p-value is correctly interpreted as “the probability to get this test-statistic or more extreme, if the null hypothesis is correct”.

The lmerTest package provides methods to calculate degrees of freedom for the F-distribution, in a specific manner not supported by the developers of the lme4 R-package, for mixed-effects models with unbalanced designs. This discussion, for how the degrees of freedom of the test-statistic should be calculated, differs for LMMs and GLMMs. I refer the author to the excellent texts that Ben Bolker has written on this subject, e.g.: https://bbolker.github.io/mixedmodels-misc/glmmFAQ.html#why-doesnt-lme4-display-denominator-degrees-of-freedomp-values-what-other-options-do-i-have. As such, my suggestion to make this paper more interesting and relevant, is to include an unbalanced design in the simulations. Again, to summarize, it is a known result is that the fixed-effects estimates will be unbiased when the model is misspecified and a random-effect is omitted (and as a result, so are the test-statistic and the accompanying p-values
For a paper that attempts to explain the difference in fixed- and random-effects modeling, the author surprisingly rarely mentions technical details that are important to understanding that difference. For example, for fixed-effects the likelihood is maximized. Whereas when including random-effects, the joint likelihood is marginalized w.r.t. the random effect, while maximizing with respect to all parameters. Please elaborate in the text.

The author includes a case study to appeal to the applied nature of the target audience. However, the procedure used is overly complicated and doesn’t address some of the issues that arise due to the hierarchical nature of the data, in a non-parametric bootstrap. In various places the author states that “the true values of the parameters are unknown”, which takes away any relevance that this section has to the manuscript. I make suggestions in the detailed comments below on how this could be improved.
Validity of the findings: The author extensively presents the issue with p-values in mixed-effects models in the discussion from an ecological perspective, but unfortunately fails to clearly identify and discuss the problems it has. In a balanced design, such as here, with normally distributed residuals such as here, it is well known that the test-statistic is exactly F-distributed with known degrees of freedom, so that it nullifies any discussion around p-values in LMMs. Unfortunately, the author has focused completely on a balanced design, but fails to realize the estimates of a linear regression are unbiased when the random-effect is omitted, in such cases. There is plentiful statistical literature available from the last 50 years, or so, on mixed-effects models and balanced designs, though the author does not seem to be aware of this. If the author insists on keeping the manuscript focused on a balanced design, they should check that statistical literature for a deeper discussion on the matter, to provide a stronger justification here.
Additional comments: Next follow some line-by-line detailed comments, though I suggest to thoroughly revise the whole manuscript. In general, the paper reads as if it lacks statistical sophistication. While I appreciate that it should be accessible to applied researchers, I suggest improving the text so it does not appear as if the subject has been “dumbed down”, as it is inherently a complex and technical subject that the author is attempting to address that statisticians have struggled with for decades.

Detailed comments
Line 12: remove generalized, or include GLMMs in the study design. This “oversells” what the manuscript is about.
Line 17: Remove ecological from “simulate ecological datasets”. There is nothing ecological about a simulation, though it might be a realistic representation of ecological datasets (if so, write that).
Line 19: remove should and similar strong language use throughout the manuscript
Line 23: correct generalized to general.
Line 25: please make sure to use correct language use. Correct “LM uncertainty” to “uncertainty in parameter estimates of LMs” or similar.
Line 26: remove never or provide a range of references that prove this.
Line 31-32: please remove this line “blindly following guidelines” or provide various references that prove that this is what ecologists do (rather than what the author thinks ecologists do)
Line 38-43: this is a very long and difficult to read sentence, please improve.
Line 46: I doubt that both Bolker references are required here,  one should be sufficient.
Line 49-53: this manuscript has little to do with accounting for imperfect detection, N-mixture models of mark-recapture methods so I fail to see the relevance of this paragraph. Please remove.
Line 55: remove “a regression type analysis", this language use is too informal and redundant
Line 56: please correct “data generating processes” to “distributions”. The data generating process envelops both the model and the distribution, while here the author only refers to the distribution.
Line 58: remove “mean-centered”, this is not a requirement for linear regression, nor is it usual to do so.
Line 60: remove “simply”
Line 67: the author their argument for random-effects is that they account for nuisance variation, using fixed-effects to account for unexplained variation here, is then misspecification of the model (as the author defines them as random-effects).
Line 76: replace “should” with less strong language
Line 79-81: the author argues, without any references or clarification, that modelers should use random slopes. This is context dependent, and this is a too general statement. Please remove, or improve by clarifying considerably (I suggest the former).
Line 97: please provide some more/other references than Harrison. A large part of the author their argument (also further on in the text) is build on Harrison 2015, while they argue that it is a problem that has wide scope and evidence, so using a larger variety of references to show that shouldn’t be an issue.
Line 102: please provide some references on this matter, as this is again a very bold statement.
Line 107: also referred to as “practical identifiability”, see e.g. Wieland et al. 2021 titled “On structural and practical identifiability”.
Line 107: the author in various places argues in a certain way, but fails to see that it is straightforward to argue opposite. Here: there are plenty of cases where residual (random-effect) variances are interesting to inference. Arguing in such a way distract from the novelty of the manuscript so that it fails to convince the reader. Please improve.
Line 118-120: again, the author argues that there is certain practice in ecology, for the application of models, but fails to provide a reference. A lot of these statements seem to be built on conjecture. Please improve.
Line 121: I think you mentioned this earlier, but this isn't about pseudoreplication: that is being controlled for whether a fixed or random effect is used regardless.
Line 146: (equation 2): for a normal distribution where the mean is assumed to be zero (as in all random-effects, because it is common practice to reparametrize as such for the sake of convergence) please write a zero, not a mu symbol.
Line 150: remove mu.
Line 152: this applies to the whole section. I suggest adapting the simulation so that the variance of all terms sum to one, to that their contribution can be directly interpreted in terms of R^2.
Line 160: this means that the variance of the residual is (very) small, so that simulated datasets are (very) simple, and the contribution of fixed- and random-effects provide (very) good fits. It makes the whole simulation set-up not very convincing. Please increase variance explained by the random-effects and in the residuals. Similarly, for variances close to zero the normal distribution becomes very “spiky” so that things can get a bit wonky numerically.
Line 185: please remove #LMM:, as it is redundant. Similar for the second code block. I would also suggest not assigning a different model to “m1” and “m2”, but to uniquely name them, as they are different models. Further on in the manuscript this has been done correctly.
Line 190-191: this sentence reads a bit awkward, please improve. We don’t “fit sites” in ecology. We fit a model to our data.
Line 192: add is before if and remove is after the comma
Line 203: please add to clarify that these are still intercepts, though. The variance of the random-effect can as such still be accounted for, by setting the sample variance of the vector of intercepts to the variance of the random-effect.
Line 204: remove this fixed-effects explanation. This is explained earlier in the manuscript and thus is here redundant.
Line 206: in various places in the manuscript the author emphasizes large numbers of the simulation as if they themselves are impressed by it. I would like to note that these kinds of numbers are common for statistical simulations, and the reader is not interested in reading them all throughout the manuscript. Though necessary to report the number of simulations, if the author really wants to emphasize other of these numbers, please do so in a single place. Better yet, just leave them out as it is very distracting.
Line 211-216: I fail to understand why the author is re-sampling p-values from simulated models. Instead of making this more complicated than it has to be, the author can draw a histogram of p-values from the simulated model, which should follow a uniform distribution, with 5% of p-values being smaller than 0.05. Note, that for a single trial, the p-values will follow a Bernoulli distribution with p=0.05, if the author wants to perform a formal test of some kind.
Line 218: the author clearly wants to simulate a dataset realistic for ecological purposes, but this entire case study fails to convince as the author themselves emphasize, on multiple instances, “the truth is not known”, making this whole section feel redundant. My suggestion is to do this as is common in statistics: fit a model to the data with the desired terms, predict using that model, and consider the first fitted model as the truth. That way, the simulation is ecologically realistic, and the true parameters are known. In essence, please revise this whole paragraph/section.
Line 234: the linear model is not in “base”, it is in “stats” which is distributed with the core of R, just as “base”. It is important to get the details right, this is very sloppy.
Line 248: various instances the author uses the word “resurrect”. It’s meaning in this context is not clear to me, please swap with something more appropriate.
Line 254: please be clear, this “uncertainty” is variety in the simulation. This helps for inexperienced readers that might confuse this with the standard error retrieved from a model object. If the target audience is applied ecologists, it is important to describe these details as clearly as possible.  Currently, that is not the case.
Line 261: correct mean to intercept.
Line 263: the author uses the word “bias” on various places throughout the manuscript, but never actually calculates e.g. bias, or Root mean squared error, or some other metric. Please correct language use or include such a calculation, so that bias is actually presented.
Line 255: the percentages are also numbers I (personally) don’t care for. I can read these things in the figure, as the actual decimals are (truly) irrelevant to the arguments made here. Please remove, overall the manuscript will become a lot cleaner, neater, and in general easier and more enjoyable to read.
Line 265: again, talking of bias but providing percentages rather than bias. Please correct. Also, how important would this bias be, if we would be making inference on the variance parameters, which is one of the main points the author makes: if we don’t infer on the variance parameters everything is fine. So what if we do? Is there really any problem?
Line 268: again, these numbers are not interesting to me. If the author wants to present bias, then present a bias metric, not a percentage.
Line 280: be clear which type-1 error rate is meant here. Type-1 error rate of the test-statistic for the fixed-effects slopes.
Line 281: probability type-1 error? It’s unacceptable for a manuscript on p-values to contain mistakes in the presentation of the meaning of p-values, make sure this is correct throughout the manuscript.
Line 285: this whole section is redundant at the moment because of how this has been set up. Please read my previous comment on this and revise.
Line 293: remove 10.000
Line 303: this sentence doesn’t read right. The levels of an accompanying random effect have fewer than five levels?
Line 304: what was your expectation for the type-1 error rates? It would be helpful if that was included in the end of the introduction.
Line 319: adding the mu and sigma symbols doesn’t add anything here, please remove. Same for the next line.
Line 324: remove quite
Line 330: how often do ecologists report variance parameters of random-effects? Is this really an issue? The author has failed to convince me on this (and some other) fronts.
Line 337: a higher probability of p-values? I think you mean proportion here.
Line 347: many readers might be put off by such statements, as the paper might seem (too) subjective, please improve.
Line 349-362: remove this whole paragraph. The author has clearly failed to see the issue with the lmerTest R-package and needs to consider his issue more deeply. By using the R-package the author does send the message that it is OK to do this, whereas they seem to argue that it isn’t. Confusing.
Line 388-389: remove this sentence. I really think a more objective view of this subject is required in this text.
Figure legend 4: please refrain from drawing inference oor conclusions in figure legends. (and reduce the size of the figure legend).  Here, the author just needs to explain what is presented. The reader can, and should, interpret this on their own, given that sufficient information is provided on the context of the figure


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: SHOULD I USE FIXED EFFECTS OR RANDOM EFFECTS WHEN I HAVE FEWER THAN FIVE LEVELS OF A GROUPING FACTOR IN A MIXED-EFFECTS MODEL?
Review round: 2
Reviewer: 1

Output:
Basic reporting: Basically OK.

MINOR COMMENTS

l. 14 "[so] few levels"

l. 20 "[the] coverage probability"

l. 24 "simulations/model structures" → "scenarios"

l. 30 "blindly" → "routinely" ("blindly" is evocative, but seems too strong. "Automatically" ?)

l. 64 "date and time of sampling" are probably not the best examples of fixed-effect nuisance variables, as both could easily also be treated as categorical grouping variables in a random-effect term. Size, age, or sex of an individual organism would be more typical/less ambiguous (admittedly I can't immediately think of good parallels in a climate change or anthropogenic noise context).

l. 72 "usually" (stronger than "often" - in reality it's "almost always")

l. 73 "which is not the same distribution" is vague: does it refer to the "data-generating process", which is not a distribution (and hence can't be "the same as" the response distribution) ? Do you mean the conditional distribution?

l. 94, 96; I found it interesting that the author has contributed to studies that both do and don't follow the ">5 levels" rule ...

l. 103 "In many cases,"

l. 114-15 "in ecology [when the grouping variable has too few levels] is ... rather than [as] random effects"

l. 115 "and" splice (split sentence or use a semicolon?)

l. 123 (and 226, 261) I have strong feelings about the use of "warnings" vs "errors", which have specific technical meanings in R. Singular fits in lme4 lead to *messages* saying that the fit is singular. Fits with other packages that estimate RE variances on the log scale typically lead to *warnings* about convergence. Perhaps just "singular fits" ?

l. 128 Please specify the lme4 package version used.

l. 143 It seems odd to use a model with intercept equal to zero. There's nothing statistically wrong with it, but if we're thinking about the response variable as "tree height" then it's weird. You can always say "it's mean-corrected tree height", but that seems to introduce an extra step. (If I'm not mistake the response to reviewers stated "Yet, it is my understanding that one needs a response with both negative and positive values for linear regression", which is plain wrong ...)

l. 147 "Note that" → "While" ?

l. 163-4 "a [strong] positive relationship ... weak [positive] relationship" (is there a biological idea behind the second relationship? A trophic cascade?)

l. 170 Using both back-ticks and typewriter font to refer to package names seems redundant (back-ticks should probably only be used in very specific contexts where users are used to "markdown" conventions)

l. 173-174 it's not clear why both forms of the equation are included here. I can appreciate that the author wants to convey both the specific and general forms of the question, but this approach seems clunky.

l. 211 "centered on " → "close to" (you can say either that the distribution of estimates is centered on the true value, *or* that the means are close to the true value ...)

l. 214-216 it would be good to include some typical numerical values in the text here so the reader isn't forced to look at the figure to know approximately what "high" and "low" mean.

l. 230 missing space "that fixed"

l. 253 arguably *any* rule of thumb/cutoff for how many levels is enough will be arbitrary???

l. 258 "there do appear to be some disadvantages"

l. 262 "sample sizes"

l. 315 This is the wrong citation for Bates et al.; please cite the JSS paper (e.g. 'citation("lme4")' in R)

Table 1. There are few enough distinct categories here that a graphical presentation might be nice. I'm thinking about something like

1. reorder "random_effect" variable by mean nlevels (using reorder())

2. ggplot(data, aes (x=nlevels, y = random_effect)) + stat_sum() +
  scale_x_log10()

(stat_sum() will be useful for distinguishing overlapping points (there are two studies with {sites, 6}))

Figure 1. It would be useful either to put confidence-interval ribbons on the individual lines, or to put a CI around the expected 0.95 value. (I think this will be approx ± 2*sqrt(p*(1-p)/n) = ± 0.004, which actually seems surprisingly small; if the sampling error is this small, it makes me wonder about apparent artifacts like the non-monotonic pattern for LMM N=60?)

I rarely find tables of numbers useful, I always prefer graphical summaries.

Figure 2. It's impossible to distinguish the line type in the legend.

Figure 3. Are the confidence intervals shown the *means* of the CIs computed for each simulated data set (i.e. the means of the lower and upper limits), or ... ??
Experimental design: l. 173-174 The formulas here are wrong (i.e., don't match the model described in the text/on l. 187) because R implicitly includes an intercept in the model unless +0 or -1 is included in the formula.

l. 155 it's interesting that the author chose to simulate a balanced, nested design, i.e. a design where the predictor variables vary only across levels of the grouping variables (sites), not within sites, and where there is an equal number of observations per site. As pointed out by Murtaugh (2007), this is a case where it's arguably better (given that we're not interested in quantifying variance) to collapse the data by taking the mean tree height in each site, at which point the model collapses to a single level and we don't even need mixed models!

Murtaugh, Paul A. “Simplicity and Complexity in Ecological Data Analysis.” Ecology 88, no. 1 (2007): 56–62.
Validity of the findings: The revised version of this paper is considerably improved. I still think the pros and cons of 'dropping' random effects (i.e. coding a grouping variable as fixed rather than random) could be stated more clearly; that the scope of the simulations is rather narrow; and that the paper could use a more solid theoretical foundation.

1. The primary thing missing from this paper is a clear, explicit statement of the advantages and disadvantages of the two approaches (random vs fixed grouping variables). For example:

* LMs are simpler to use (and hence less prone to user error), and faster to compute.
* Because they are conceptually simpler, metrics like R^2 are easier to compute.
* They avoid concerns about singular fits.
* They preclude users from making possibly inappropriate generalizations to unobserved levels of the grouping variable.
* They eschew assumptions about the distribution of the random effects.

* LMMs are (often) conceptually correct models of the system.
* They allow generalization to unobserved levels of the grouping variable.
* In principle LMMs can provide RMSE and increased precision (I don't see an analysis of the relative efficiency/width of confidence intervals for LM vs LMM, which would be useful; Fig 2 shows that over this range of scenarios the RMSE advantage is weak at best).
* In a study with multiple analyses with widely varying numbers of grouping variable levels, it would be more consistent to use LMMs throughout rather than switching from LMMs to LMs at some threshold value.

2. It would be extremely useful to do a subgroup analysis that compares the singular and non-singular fits. If the results from singular fits are not inappropriate (biased, undercovered, etc.), that would be an important guide to users to know if they should worry when they get a singular fit.

3. Please give at least a brief description of the conclusions of the "limited" previous studies that have tackled related questions (i.e. Oberpriller et al., Clark & Linzer, Gelman & Hill, Bolker 2009).

Figure 1. It is strange, and very concerning, that the coverage for the 'weak' slope effect should *decrease* as the sample size increases. This seems extremely hard to explain; when the statistical model matches the simulation model, the coverage should converge to the nominal level as the sample size increases. Please double-check the code/results, *or* develop and present a theoretical explanation as to why this pattern emerges.
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: SHOULD I USE FIXED EFFECTS OR RANDOM EFFECTS WHEN I HAVE FEWER THAN FIVE LEVELS OF A GROUPING FACTOR IN A MIXED-EFFECTS MODEL?
Review round: 2
Reviewer: 2

Output:
Basic reporting: The author has done well in addressing the many detailed comments, especially related to strong language in the manuscript. Largely, the author has removed any reference to p-values and has a such addressed most comments related to that subject. There was a case study included in the previous version of the article, which was also removed in response to a comment. As such, the article now fully focuses on a simulation study for the assessment of bias in fixed-effects parameter estimates in the presence of a random intercept term, with an increasing number of levels.
There are still some minor textual errors that need addressing, and I have two larger comments which need careful consideration.
Experimental design: -
Validity of the findings: One comment from my previous response has not been addressed to satisfaction. This relates to the difference of mixed models for use of balanced versus unbalanced design studies. My comment on the original submission related to the inclusion of p-values, their application in mixed-effects models, and the asymptotic distribution of the test statistic under a balanced design. Though the author addressed the difficulty of p-values in mixed-models by removing large parts of the article, the author still seems unaware of the deeper issue that underlies that discussion. Since the author explicitly decided to not expand the article by including an unbalanced design, this is now an issue more central to the whole article. For clarity, I refer the author to the classical text of Searle (1997), but discussion of this topic can also be found in more recent textbooks such as Wood (2017), or in general in statistical textbooks on linear modeling. It is a known result, that in the case of a balanced design, the fixed-effects parameter estimates are independent of the estimator for the residual variance. If one adds any random-effects terms, such as a random-intercept, this remains the case. For example, Wood (2017) writes on page 74: “hence, in a mixed model context, we can still use fixed effects least squares methods for inferences about any fixed effects whose estimators are independent of all the random effects in the model”. As such, I largely suspect that any deviation from that known result in this article is due to the software implementation. The author can address this by altering the study design to that of an unbalanced design, e.g., by setting the number of observations for half of the levels in the random effect to fewer observations (perhaps 2 or 3).

My second comment applies to the removal of the ecological example. In the previous version of the article, the example did not add (much), as the author questioned the usefulness of the example in the text, by stating e.g., “the truth is not known”. Since the target audience of this article are applied ecologists, and the author has explicitly stated the interest of conveying this complex subject in an understandable way, I urge the author to re-implement the ecological example, but to improve it compared to the original submission. The example has the potential of making the subject a lot more understandable to most readers, though it does need to be designed as such. For example, the author could instead discuss how following the 5-level rule might change inference in a real data example, to convince the reader of the issue from a more practical perspective. In case the inference is the same, then perhaps address the issues of numerical stability of the fitting process.

Please note that there are no means (referred to as mu in the manuscript) for the random-effects, as the random-effect is assumed to have a mean of zero (as stated in eq 1). I suppose the author intends to refer to the best linear unbiased prediction (BLUP) of the random effect, which also relates to my comment on line 2 below.

Lastly, I had trouble connecting the figures to the text, as the images were not named or numbered in any way so that they could easily be related to the text.

Below follow more detailed comments to the text, though I suggest to first consider thoroughly revising the manuscript based on these main comments.

References:
Searle, S. R., & Gruber, M. H. (2016). Linear models. John Wiley & Sons.
Wood, S. N. (2017). Generalized additive models: an introduction with R. CRC press.
Additional comments: Detailed comments:
Line 2: The author has chosen the title to include the terms “fixed” and “random” effect. Yet chooses not to further expand on the details between the differences (this was one of my comments on the previous version). I urge the author to re-consider: the difference between fixed- and random-effects is often unclear to ecologists. Yes, it is a complex and detailed issue, but at least the author can mention it in a technical context (maximizing vs. marginalizing) and provide the reader the option to continue reading on that elsewhere.
Line 14: remove such, the whole point is that at 4,6 or 7 levels the estimation of the random-effect could also be difficult: it’s a rule of thumb.
Line 18: replace “and” by “to” and remove “too”
Line 20: e.g., should be i.e.,
Line 20: change “although” to “the”
Line 21: remove “in some cases”, “may” before in the sentence is sufficient to indicate speculation
Line 23: change in brackets to “when they are nuisance parameters..”
Line 24: change forward slash to “and”
Line 48: change “model correlations” to “account for correlation between”
Line 49: I have not seen random-effects referred to before as “varying effects”. Is this addition necessary, I don’t think it is widely referred to as such in ecology?
Line 55: it is unclear to me what is meant by “body condition residuals”. Potentially confusing language use with “residuals” in the context of a regression
Line 58: should mixed effects be italized?
Line 64: I still don’t particularly agree with this explanation. Date or time of sampling is one of those examples that can very well be understood as a random effect. Is there a more clearly distinguishable example the author can come up with, that is (essentially) never used as a random effect? Habitat perhaps?
Line 66: I don’t follow the author their meaning with this sentence
Line 70: the sentence after the reference seems disconnected with the previous, but they also seem to convey the same message. Is it possible to improve this?
Line 71: “Random-effects are random” seems to be a (too) obvious statement. Please change to “Random-effects are assumed to be drawn…”
Line 86: change “this” to “the”
Line 88: missing a word “too few draws from distribution”
Line 89: add “at least” before five
Line 95: why do they ignore the rule if they acknowledge its existence? Can you provide context to this statement? It seems relevant to your argument.
Line 98: I’m confused about table 1, only one study included a random effect with fewer than 5 levels, is that correct? Also, why does the table have 27 rows if there were 29 studies with random effects?
Line 103: multiple random effects implies multiple variance parameters, yet variance here is singular not plural. Do you mean a single random-effect with multiple levels?
Line 110: change “it is” to “can be”
Line 113: uncertainty of predictor variables is a different problem entirely (error-in-variables). I think you mean uncertainty of parameter estimates.
Line 114: we don’t “fit blocking factors”. We treat them as fixed-effects rather than as random-effects, please correct.
Line 129: add “the” before “R package”
Line 137: eq 1 and further lack the explicit normal distribution for the residual, epsilon. Also, can we get the equation numbers on the same lines as the equation?
Line 149: relates to a previous comment with respect to R^2 interpretation. You can increase the magnitude of the variances, and still interpret proportionally. They don’t need to all sum to one.
Line 154: please improve so that this is a correct and full sentence. Also, equations are part of sentences and need a full stop (or comma) after them consequently
Line 157: it is more common to parameterize the normal distribution with variance, i.e., sigma^2.
Line 159: I don’t think you defined subscript j before
Line 162: space missing after the second brackets. Also, sigma is usually referred to as the standard deviation, not the variance.
Line 170: remove quotes around R-package names
Line 180: I think should be n here (total number of levels)
Line 189: beta is a parameter, not a term
Line 213: extra space after which
Line 215: I would never consider slopes “strong”. First, this is a bit subjective language use, second, the slope represents the effect of the predictor and has no effect in and of itself.
Line 215: please refrain from similar subjective language “high”. I would suggest changing to “higher” as its relative to LMMs
Line 217: I miss the general conclusion that coverage probability was lower for LMMs than for LMs
Line 218: RMSE of fixed-effects parameter estimates, I think? Please clarify
Line 220: Please add confidence interval bands to all figures, otherwise it’s difficult to draw such conclusions
Line 220: change “strongest” to “largest”
Line 222: The random effect has a mean of zero, I think you mean the BLUP here too? Please see my other comments on this before
Line 230: typo
Line 231: remove (n>5), it doesn’t add anything here
Line 232: extra space after level
Line 232: please improve “random effect sigma” to “random-effects variance” or what you actually refer to here
Line 248: there are no mu’s in the random-effect (well, they’re zero) please clarify (see also comments before)
Line 265: please note that specifying a random-effect as fixed-effect as here increases the number of parameters in the model
Line 279: change “as researchers” to “field”
Line 280: again, this requires consideration of marginalization vs. maximization


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: EFFECTIVE ASEXUAL REPRODUCTION OF A WIDESPREAD SOFT CORAL: COMPARATIVE ASSESSMENT OF FOUR DIFFERENT FRAGMENTATION METHODS
Review round: 1
Reviewer: 1

Output:
Basic reporting: See ahead
Experimental design: See ahead
Validity of the findings: See ahead
Additional comments: I have carefully read the manuscript by Kim et. al. entitled: “Effective asexual reproduction of a cosmopolitan soft coral: Comparative assessment of four different fragmentation methods”.
The manuscript presents experimental approaches for asexual propagation of a soft coral. I praise the authors for putting together the results on this subject. However, I have some critical comments addressed below:
1.	I wonder what is the scientific evidence for claiming that X. umbellata is a cosmopolitan
soft coral. Google says for this term: “A plant or animal found all over the world”. This is definitely (!) not the case for this soft coral. The mistake should be corrected and the current biogeographic distributional boundaries of the study species has to be addressed correctly with appropriate references.
2.	 The rational of the study should be addressed from a different perspective which unfortunately has been ignored in the manuscript. Xeniid soft corals have been found to be invasive, replacing other benthic reef organisms including stony corals included, following reef deterioration etc. The recent literature indicates that xeniids have become dominant benthos in places where that did not exist before. In addition, studies have shown that they tolerate global change conditions and shift in community structure is expected on may reefs to become soft coral dominated. All these topics have been addressed in the scientific literature, but unfortunately not mentioned in the manuscript.
3.	The above (2.) may challenge the concept presented in the manuscript arguing the environmental and conservation arguments ask for adequate asexual propagation methods of xeniids. But, why to transplant them on denuded reefs if they are considered to be successful colonizers as well as fugitive species? In addition, their prolonged reproductive season and high fecundity as shown in several studies, but not mentioned in the current ms, significantly contribute to the immense success and even massive space occupation on the reef.
4.	The hobby reef aquarists usually want to control Xenia spread in their tanks. Their successful development in the tanks also diminish the practical value of the current results. I wonder why the authors did not refer to this point in the text.
5.	Unlike nephtheid soft corals, xeniids have no RLPs. Their attachment to hard substrate is conducted by natural glue, yet of unknown nature
6.	The authors missed several studies on soft coral husbandry which are so relevant to their study (e.g.  Aquaculture Research, 2010, 41, 1748^1758, Natural Resources Vol.07 No.06(2016), many others on the red coral and other gorgonians). A thorough review of such references is required in order to frame the current study and to pin point its novelty.


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: EFFECTIVE ASEXUAL REPRODUCTION OF A WIDESPREAD SOFT CORAL: COMPARATIVE ASSESSMENT OF FOUR DIFFERENT FRAGMENTATION METHODS
Review round: 1
Reviewer: 2

Output:
Basic reporting: The language is clear and relevant literature is referenced.
Experimental design: The experimental design is clearly described and the research question and the purpose of the study are well defined. Methods are effectively described and could be replicated.
Validity of the findings: The author cited relevant research that shaped the design of the experiment and in support of findings. It remains unclear how effective this practice will be in a field setting, but the purpose of the study is clear and the targeted questions are effectively tested and answered through the lab trials.
Additional comments: While the findings of this lab-based study suggests that the plug mesh method is the most effective approach, it should be considered that this may only be true in an aquarium setting. Without having run field trials it may be difficult to determine the challenges and success involved with using this approach on a coral reef, where animals, surge, and other environmental disturbances could influence the effectiveness of this method. It should also be considered that best practices for restoration involve minimizing the amount of artificial materials left on a reef, so its possible that one of the methods that appeared to be less successful in the lab setting may be more suitable for the field setting.

It is unclear if the measurement for fragmentation time was completed by a single individual or multiple participants who could have varying levels of experience in this type of skill.

If oxygen fluxes and pulsation rates served as a proxy for health, then survivorship should be one of the parameters being evaluated in this study. Although it was mentioned that mortality occurred among some of the fragments, it is a significant indicator in  measuring the success of fragmentation and attachment method, especially considering that mortality was so high among the glue method group.


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: DNOISE: DISTANCE DENOISING BY ENTROPY. AN OPEN-SOURCE PARALLELIZABLE ALTERNATIVE FOR DENOISING SEQUENCE DATASETS
Review round: 1
Reviewer: 1

Output:
Basic reporting: A software that uses the properties of coding genes to filter erroneous reads has been desired for some time now and the authors succeed in bringing this research forward.

The entropy corrected denoising algorithm, benchmark and discussion of DnoisE has already been published in Antich et al.  2021. Although they mentioned that it is a beta-version, it is not exactly clear what has been added to the software since then. The novelty seems to be the description of parallel processing, even though parallel processing was already available since the publication of Antich et al. 2021 in April. Maybe the authors should state more clearly what this manuscripts adds additionally.
Experimental design: The presented method is relevant, closes a current gap and is important for the further development of the field.

The entropy correction is a sound way to utilize the coding region properties of genes like cox1.

The available software on github does not provide any tests to show that the program actually works as intended. I suggest adding tests for core functionalities, since I have observed bugs during my investigation (see section 4).

Entropy correction has been benchmarked in Antich et al. 2021. The authors used a dataset which was filtered beforehand by excluding sequences that do not align properly due to, for example, indels or offsets. The authors mention on the lines 188-189 that in practice the distance is the same, if there are no indels and the sequences are aligned. This seems to be an important prerequisite for the usage of this software and should be stated more clearly. Depending on sample and primers, offsets might be frequent and many taxa do have indels in the cox1 fragment. It is also mentioned in Antich et al. 2021: “We used a dataset of fixed sequence length and eliminated misaligned sequences. The correction for codon position would be more complicated in the presence of indels and dubious alignments.“
-> Therefore I strongly recommend to mention in the manuscript and on the github README page, that such a prefiltering has to be done before using DnoisE.
Validity of the findings: The distinction between correct and wrong merged sequences seems generally reasonable. Although a representative mock community would be the only way to be somewhat sure that the results are valid. Such a mock community would need to have many specimens per species and a wide range of differing biomasses per specimen. I see that such a mock community is not available at the moment and might never be. Because of that I suggest adding a remark that this approach needs further investigation and other benchmarks.

Regarding the benchmark: How has it been decided which genetic code was used to translate the sequences from nucleotides to amino acids, if there were the same number of stop codons?

Has each denoised sequence been translated afterwards with the same genetic code across the different denoising strategies (DnoisE, Unoise3, dada2)? This is not clear from the benchmark of Antich et al 2021 and could lead to differing decisions regarding the correctness of a sequence.
Additional comments: Line 283: Change “Is it” to “It is”

Line 318-319: No samples provided

Some comments in the source code are not in english and should be translated.

I found some bugs as I tested DnoisE:
The -x option did not work.

python3 --version
Python 3.8.10

command: python3 ../DnoisE/src/DnoisE.py -i in.fa -o out.dout -F F -c 4 -e 0.3468,0.159,0.709 -y T -x 2

stdout:
starting to denoise
['-i', 'in.fa', '-o', 'out.dout', '-F', 'F', '-c', '4', '-e', '0.3468,0.159,0.709', '-y', 'T', '-x', '2']
Denoising in.fa file
Output files will be named out.dout*
Fasta output file: False
Running with 4 cores
E1: 0.3468
E2: 0.159
E3: 0.709
Is entropy taken into account: True
Traceback (most recent call last):
  File "../DnoisE/src/DnoisE.py", line 31, in <module>
    de.read_parameters(argument_list)
  File "/home/user/reviews/peerj/DnoisE/DnoisE/src/denoise_functions.py", line 198, in read_parameters
    self.initial_pos = int(current_argument)
ValueError: invalid literal for int() with base 10: '-x'

Therefore users are not able to use it on datasets that have a different then the default value. Since there is wide variety of primers and start positions, this seems to be crucial option to work as intended. Not every user will be able to do modify the default value in the source code, hence this needs to be fixed if the software should be used with a variety of datasets.

To_uniq_line_fasta.sh does not work. It also has a wrong usage message

entrpy.R does not work if the input file ends with .fas:
Error: unknown input file format!
Execution halted

At least on my machine, the entrpy.R script consumes quite quickly too much memory and the process gets killed, or I get the following error message (tested with a 500 MB text file):
Error in total + rebost : non-conformable arrays
Calls: entrpy
Execution halted

I would suggest fixing this issue and if not possible: mention the problem on the github README. This is of course dependent on the data and hardware, but if the user is warned beforehand he could shrink the data by only using sequences with size > 1, or try it on a computer with more RAM.

References:
Antich, A., Palacín, C., Wangensteen, O. S., & Turon, X. (2021). To denoise or to
cluster, that is not the question: optimizing pipelines for COI metabarcoding and
metaphylogeography. BMC Bioinformatics, 22(1), 177.
https://doi.org/10.1186/s12859-021-04115-6


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: DNOISE: DISTANCE DENOISING BY ENTROPY. AN OPEN-SOURCE PARALLELIZABLE ALTERNATIVE FOR DENOISING SEQUENCE DATASETS
Review round: 1
Reviewer: 2

Output:
Basic reporting: The authors present a software package, called "DnoisE", that implements a known denoising strategy (UNOISE2/3) in an open-source package, with the addition of a novel strategy that should increase the performance when analysing coding markers.
I consider this software a welcomed addition in the tool shed of the bioinformatician analysing metabarcoding data, in particular for its claim of being better suited for less popular markers, suck as COI.

The manuscript introduces the core concepts (Background), the algorithm (Workflow) and the benefits of parallel processing (Benchmark).
Experimental design: The "Workflow" paragraph can be expanded, as it should be noted that UNOISE is only available as a closed-source commercial package (USEARCH) and its description is only available as a non peer-reviewed pre-print, that focuses on UNOISE2 and - from the author's website - UNOISE3 is only described as an improved set of defaults (as far as I understood).

There is a lack of an analysis of the accuracy and sensitivity of the program if compared with its natural ancestor (UNOISE3) and its most used competitor (DADA2), and the "Benchmark".

The benchmark section describes briefly a comparison performed with a published dataset, but fails to provide the code used to run the packages and to evaluate the differences in stop codons.
To benchmark the novelty of the program (i.e. analysis of coding regions with information entropy) can be evaluated with a well known mock community.
Validity of the findings: The DnoisE program is an interesting software, but the manuscript does not provide a sufficient exploration of its application domain and its sensibility/sensitivity/F1 etc.
Additional comments: As a tool user and tool developer, I find the structure of the software and its repository quite poor and distant from the standards of packages released in the last decade.

As a user, it's legitimate to expect a facilitated installation, for example via Miniconda (I'm glad to provide guidance to package the software for Bioconda), and an author controlled set of versions ("releases" in github), to increase the reproducibility.

As a developer I found the code poorly structured and not documented, lacking input validation both for trivial usages (e.g. providing FASTQ files instead of FASTA files) and for more delicate formatting issues: the output of "usearch -fastx_uniques XYZ -sizeout" was not accepted if the sequence names contained non alphanumeric characters (e.g. ">MSED1-end.42;size=3370;").

The absence of automatic testing will increase the risk of introducing unexpected behaviours in future releases.

The software is the main output of this research, and I would welcome an improved adherence to widely adopted criteria for usability and reproducibility.

VSEARCH, published in this journal on 2016, is a great example: https://github.com/torognes/vsearch.


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: DNOISE: DISTANCE DENOISING BY ENTROPY. AN OPEN-SOURCE PARALLELIZABLE ALTERNATIVE FOR DENOISING SEQUENCE DATASETS
Review round: 2
Reviewer: 1

Output:
Basic reporting: -
Experimental design: -
Validity of the findings: -
Additional comments: At first, I was very happy to see the improvements of DnoisE and I think the authors did in general a great job addressing our concerns.

However, I have noticed a few things that I would like to describe:

I tried DnoisE with the provided example files and also with my own data. Using my own data, there was no difference between the output if entropy correction was enabled (-y) and if not. It resulted in the same sequences. This seems to me as a strange result and I wonder how this could happen? I would offer to provide my test data. If needed, please contact me via email: n.noll@leibniz-zfmk.de
The example from your github repository did however show different results. But not as expected. Here we find less sequences if entropy correction was enabled. This is contrary to the findings of Antich et. al 2021 and I wonder if this is due to the different dataset or is it because of a change in the entropy calculation?

After I installed the program with ./install.sh the binary did not work with the following error message:
./DnoisE -h
Traceback (most recent call last):
  File "src/DnoisE.py", line 12, in <module>
ModuleNotFoundError: No module named 'denoise_functions'
[15164] Failed to execute script 'DnoisE' due to unhandled exception!

It does however work if I use python3 ./src/DnoisE.py. Therefore, I suggest fixing the issue with the binary.

The result output *denoising_info.csv seems as if it is not correctly generated. Another problem is that the output files are neither explained in the current manuscript and also not on the github page. I would expect a brief explanation of what every column name means. For example xavier_criteria.
The second column “mother_d” seems to be the name of the mother sequence, whereas d shows otherwise an integer.
The column “mother_ratio” holds the name of the mother sequence and is not a ratio

The help message displays:
y --entropy_correction a distance correction based on entropy is performed (see ENTROPY CORRECTION below). If set to F, no correction for entropy is performed (corresponding to the standard Unoise formulation)

There is no “below” and the entropy correction is not explained further. It is also misleading that no correction is performed if -y is set to F. The default of DnoisE is to not use entropy correction. Using the -y option enables it. Since this seems to be just a flag argument, it cannot be set to false and it would also be unnecessary.

If the input file is of type fasta, a semicolon is needed at the end of the header. Since the output files from usearch or vsearch do not include semicolons at the end, I would recommend allowing users to use files without these.

I could still find no automated tests that ensure the correctness of core functions or output results.

L106-L111:  It should be added that aligned sequences are needed. The entropy correction is the main novel feature of DnoisE and using it without aligned sequences this feature does not work properly.


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: DNOISE: DISTANCE DENOISING BY ENTROPY. AN OPEN-SOURCE PARALLELIZABLE ALTERNATIVE FOR DENOISING SEQUENCE DATASETS
Review round: 2
Reviewer: 2

Output:
Basic reporting: I would like to thank the authors for the improvements and for kindly addressing my questions.

I recommend a more detailed explanation of the core algorithm (as schematized in Figure 1), and a clearer comparison (in a dedicated paragraph) with the procedure previously published in Antich 2021 and UNOISE itself.

I think added clarity in this aspect is pivotal for a better understanding of the paper, especially for those who already implemented the methodology as originally described.
In particular, I recommend not to refer to the software used in Antich 2021 as "beta", as it was in fact used in production for the paper itself, and according to the authors, the changes are not expected to produce different findings.
Experimental design: no comment
Validity of the findings: In the "DnoisE performance" paragraph I suggest a more explicit comparison with Unoise.
A Venn diagram with the shared identical sequences will be a good addition.

The mention of future work with mock communities is sound and appropriate, yet the increased number in ESV detected with entropy correction can include false positives.
Considering that the method was applied previously, and the entropy correction is the unique feature of the presented tool, I think that a formal validation of the entropy-correction algorithm is required, at least with simulated reads comparing the effect of the correction and of naive approaches.
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: RECONSTRUCTING THE TRANSMISSION DYNAMICS OF VARICELLA IN JAPAN: AN ELEVATION OF AGE AT INFECTION
Review round: 1
Reviewer: 1

Output:
Basic reporting: -
Experimental design: -
Validity of the findings: -
Additional comments: This is an epidemiological study to follow the impact of universal varicella vaccination program in Japan, initiated in 2014. Two doses of vaccine are given between ages 12 and 36 months. This information is key to the findings and should be given also in the Abstract. Also the level of coverage should be mentioned in the Abstract.

The title of the paper is complicated. The main observation is a shift in age from young children to older children and teenagers. This should be reflected in the title.

The Introduction is long. It could be shortened by deleting the last but one paragraph discussing herpes zoster. This study does not address the incidence of zoster. Moreover, for a full review of the subject the one paragraph is not enough. Likewise, the corresponding paragraph on zoster in Discussion should be deleted.

The data indicate that following varicella UMV in Japan the age of catching chicken pox has shifted from young children to teenagers. This is associated with a higher risk of complications, although this study does not provide any numbers in this regard. The age shift was observed in the US twenty years ago. The main reason was insufficient vaccine coverage, as it probably is in Japan.

Still, the present experience in Japan is important and worth reporting. It should be noted, however, that the increase in absolute numbers is relatively small. There are five Figures which is a lot. Of there, perhaps Fig. 3 could be deleted and shifted to supplementary material.

The remedy is obvious, but is not much discussed. The start of the program in 2014 could and should have included a catch-up vaccination up to the age of 12 years, as has been done in some countries. At the present stage, a remedy could a separate teenager vaccination program which many countries practice. While the authors’ model predicts an increase of varicella in teenagers for years to come, this does not need to happen. The authors should be bolder in their discussion about this issue.


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: RECONSTRUCTING THE TRANSMISSION DYNAMICS OF VARICELLA IN JAPAN: AN ELEVATION OF AGE AT INFECTION
Review round: 1
Reviewer: 2

Output:
Basic reporting: The paper is well written and clear in most of its parts.

Figures presented are relevant, well labelled and described and raw data are supplied.

In the Introduction the authors provide a satisfactory background on the main epidemiological features of varicella zoster virus and on the public health issue related to varicella vaccination and its possible negative impact on herpes zoster incidence.
Experimental design: The research question is well defined, however it is not clear to me if the authors fill some gap of knowledge on varicella dynamics in the presence of vaccination. Indeed, the epidemiological dynamics of varicella observed in Japan and described by the authors are in line with what observed in other geographical settings (Taiwan, United States, etc).

Methods description can be improved by addressing my suggestions/concerns in the section "Additional comments".
Validity of the findings: No comment
Additional comments: - I have one major methodological concern. I am a little bit confused by the definition of reporting rate used in this study. In my experience, the reporting rate is commonly defined as the proportion of infections occurring within a given population, that are detected by the surveillance system. In the case of this work, I would suggest that the numerator should be the number of varicella cases reported to the NESID surveillance system and the denominator should be the real number of varicella infections (either detected or undetected) occurring in the same period within the population “served” by the pediatric sentinel sites included in the NESID system. The value of the reporting rate can be estimated through mathematical models or other approaches (see e.g. doi:10.1017/S0950268802006878 ; or  https://doi.org/10.1371/journal.pcbi.1006334).
If data needed to estimate the reporting rate in Japan are not available, one could make the simplifying assumption that all varicella infections occurring in the population served by the sentinel sites are detected by the system, i.e. the reporting rate is 100%.
Under this assumption, the total number of cases reported to the surveillance system could be “projected” to the whole Japanese population as:
casesJAPAN=casesNESID*(populationJAPAN/populationNESID)
where (populationNESID/populationJAPAN)=10% and the whole analysis could be performed directly at the national level.
I find it difficult to interpret why the authors compute the reporting rate as the ratio between cases reported within a given period and the number of newborns (I think at the national level) during the same period. As far as I understand, the underlying assumption is that all individuals will develop varicella at some point. My concern is that this “certain point” could also lie outside the time interval considered. In particular, I think that changing demography could play a role, especially in the presence of varicella vaccination that can lead to a shift of infections towards older ages and in a period characterised by changes in the birth rate.

-	Fig 3A: In the discussion you comment on the increased risk at infection among children aged 5-9yrs before 2011. Do you have an explanation for the increased risk among children of younger ages (<5 years)? In this period the birth rate in Japan was declining and vaccination was in place (even though the coverage was relatively low). This should result in a shift of infections towards older age groups (e.g. 5-9yrs). I would thus expect a declining risk among young children. A previous study (https://doi.org/10.1371/journal.pcbi.1006334) explained the increase of varicella incidence observed among French pre-school children in a period characterised by a stable birth rate and in the absence of vaccination, with an increase of social-mixing in these age groups (possibly ascribable to increased attendance rate to nurseries and pre-schools). Could this represent a possible explanation also for Japan?

Minor points:
-	Abstract, line 30: “The unvaccinated birth cohort who had never contracted varicella remained susceptible over this period”. Do you refer to the result expressed in Discussion as: “A substantial number of unvaccinated individuals born before the routine immunization era remained susceptible and aged without contracting varicella.”? If yes, please consider rephrasing the sentence of the abstract, because the message is not clear.
-	l. 88: when the cumulative number susceptible individuals  missing “of”
-	Introduction (l.109): I think that 2024 should be changed to 2033, right?
-	L.149. In equation 1 the variable C represents varicella infections (all infections, detected or not) while in Equation 2, the variable I represents infections reported to the surveillance system. Conventionally, “infections” denote all infections (including those not reported to the surveillance system), while “cases” is more widely used to denote reported cases. I would suggest switching the notation, i.e. to use in Equation 1 the notation I and refer to this variable as infections, and to use notation C in Equation 2 and to refer to this variable as “cases” or “reported cases”.
-	L.164: please report the likelihood function used to estimate the annual risk of infection.
-	Fig 1 and 4 would be probably more informative when plotting incidence rates, instead of absolute numbers (if available).
-	L. 243-245: the second part of this sentence sounds like a validation of the model, but if I understand well, the annual risk of infection is estimated using age-specific incidence rate. If this is the case, please remove.
-	Discussion: previous studies (e.g. https://doi.org/10.1098/rspb.2014.2509 or https://doi.org/10.1186/s12916-017-0983-5 ) suggest that an increase of herpes zoster incidence could be expected also as a consequence of demographic changes, and in particular as a consequence of declining historical trends in the birth rate. You could consider adding a sentence in the Discussion (e.g. after l.290-293) stating that part of the observed increase could also be related to declining birth rate.


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: RECONSTRUCTING THE TRANSMISSION DYNAMICS OF VARICELLA IN JAPAN: AN ELEVATION OF AGE AT INFECTION
Review round: 2
Reviewer: 1

Output:
Basic reporting: -
Experimental design: -
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: RECONSTRUCTING THE TRANSMISSION DYNAMICS OF VARICELLA IN JAPAN: AN ELEVATION OF AGE AT INFECTION
Review round: 2
Reviewer: 2

Output:
Basic reporting: No comment
Experimental design: No comment
Validity of the findings: No comment
Additional comments: I am satisfied with the authors response.

I have only one minor comment: I suggest the authors to replace the term "elevation" in the text and in the title of the manuscript with one of the following "increase/growth/rise".


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: THE VALUE OF DIFFUSION WEIGHTED IMAGING-ALBERTA STROKE PROGRAM EARLY CT SCORE IN PREDICTING STROKE-ASSOCIATED PNEUMONIA IN PATIENTS WITH ACUTE CEREBRAL INFARCTION: A RETROSPECTIVE STUDY
Review round: 1
Reviewer: 1

Output:
Basic reporting: The article has many grammatical errors (eg line 83, 255) and needs to be corrected.
Experimental design: 1. How and when was the DWI ASPECTS score calculated ? More details to be given.
2. Exclusion criteria on the length of hospital stay is unclear. Line 108 and Figure 1 patient flow chart not consistent.
3. Line 218, NIHSS score of 15 items needs clarification as NIHSS score has only 11 items.
Validity of the findings: The size of the infarct (low DWI ASPECTS score) indicates the severity & the extent of the infarct and the moribund state of the patient's illness. Therefore, it is understandable that the larger the infarct the chances of getting any of the complications that can occur in stroke patients including SAP may be higher. There seems to be no direct causal relationship between the two parameters studied.
Many other parameters especially CRP, DM, AF etc., if abnormal, can in varying combinations may have contributed to the development of SAP.
Additional comments: The manuscript very vague and too long and the authors are not focussing on the message they want to convey.


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: THE VALUE OF DIFFUSION WEIGHTED IMAGING-ALBERTA STROKE PROGRAM EARLY CT SCORE IN PREDICTING STROKE-ASSOCIATED PNEUMONIA IN PATIENTS WITH ACUTE CEREBRAL INFARCTION: A RETROSPECTIVE STUDY
Review round: 1
Reviewer: 2

Output:
Basic reporting: See all comments below.
Experimental design: See all comments below.
Validity of the findings: See all comments below.
Additional comments: In the study, Zhao et al investigated the association between ASPECTS and occurrence of stroke-associated pneumonia. Even after controlling for multiple, relevant confounders, most notably NIHSS, ASPECTS was still predictive of SAP. The study design is logical, the statistics sound and the manuscript as a whole is easy to read.
Comments:
1.	The study’s main finding probably only reflects that the risk of SAP increases with the extent of brain injury. It is somewhat unexpected that ASPECTS had a predictive value even when NIHSS was controlled for. This is possibly due to the fact that admission NIHSS, and not NIHSS at a later time-point, was used in the analysis. Admission NIHSS is reasonably less associated to the extent of permanent brain injury than NIHSS after a few days would be. I have no issue with the use of admission NIHSS, it is indeed the most common practice, but it could be the reason why so much explanatory value was left for ASPECTS.
2.	Why have patients that stayed less than 72 h been excluded from the analysis? Isn’t it hard for the clinician to determine beforehand that the patient will leave early? This exclusion criterion limits the generalizability of the study.
3.	When was the MRI performed, in relation to the stroke? If the MRI was performed later than 72 h, many patients will already have developed their SAP (ref: PMID: 8610305 och 10447789 och 12637700), which could bias the ASPECTS assessment.
4.	The authors need to elaborate the SAP criteria. For example: Was pulmonary consolidations a radiological sign?
5.	The authors point out that MRI may be more convenient than NIHSS, but clearly they cannot mean that NIHSS should be replaced by ASPECTS (lines 218-224)? The predictive value of NIHSS was also solid, which could be emphasized.
6.	Row 225-242: This section contains a reasoning about how different localizations could affect different functions and lead to SAP. The section is a bit vague, and the fact is that the study doesn't try to evaluate how damage in different areas could affect the risk of SAP. The exception being that the authors note that anterior and posterior stroke has the same risk of SAP. They also note that posterior stroke has a lower DWI-ASPECT-score but since they have a different scoring system for anterior and posterior stroke, it is impossible to draw any conclusions from this. In row 253-258 they do note that brain-stem lesions (in this study) are not associated with increased risk of SAP, and while brain stem stroke often comes with dysphagia it is also common in other types of stroke. Since dysphagia wasn't recorded, the conclusion "Thus, the results revealed that dysphagia did not all of the reason for SAP." is hard to draw.
7.	It is an interesting finding that while lymphopenia is associated with a large stroke (and thus higher risk of SAP), in the logistic regression it is not an independent predictor for SAP. My reasoning is that this would suggest that lymphopenia is hardly a major causal pathway by which stroke leads to SAP. Of course it may also be a result of too few subjects. Maybe they could include some comment on this?
8.	Table 3 is not easily read, and the different models don't differ in their results. It would be better to just present one of the models with a comment that neutrophils, lymphocytes, NLR, NMR, WBC are all insignificant predictors regardless of model.
9.	Further, table 4 needs a better explanatory text.
10.	Abstract: “Immume” should be “immune”.
11.	Line 108: The sentence "a length of hospital stay ＜72 hours or the onset time of AIS＞72 hours " could be clarified. More than 72 hours before what? Admission? MRI?
12.	Line 216: The sentence starting on this line seems to have been cut from the previous sentence. Rephrase.
13.	Line 258: The sentence “Thus, the results revealed that dysphagia did not all of the reason for SAP.” Doesn’t make sense. Rephrase.
14.	Line 132: Peculiar expression: "expectoration emerging"


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: THE VALUE OF DIFFUSION WEIGHTED IMAGING-ALBERTA STROKE PROGRAM EARLY CT SCORE IN PREDICTING STROKE-ASSOCIATED PNEUMONIA IN PATIENTS WITH ACUTE CEREBRAL INFARCTION: A RETROSPECTIVE STUDY
Review round: 2
Reviewer: 1

Output:
Basic reporting: See below.
Experimental design: See below.
Validity of the findings: See below.
Additional comments: Row 48: change ”immume” to ”immune”

Section in Discussion starting with ” Aspiration and stroke-induced immunosuppression…”: Sorry, but the shortcomings of the language in this section are so pronounced that it is hard to understand what the authors are meaning. Needs som serious proof-reading. For example, the sentence ” It was reported that the swallowing center within the brainstem which controls and manipulates the entire pharynx phase swallowing sequence (Sasegbon A et al., 2017).” doesn’t make sense. (Also, ”esophagus” lacks an e.)


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: SEGMENTATION OF MULTI-TEMPORAL POLARIMETRIC SAR DATA BASED ON MEAN-SHIFT AND SPECTRAL GRAPH PARTITIONING
Review round: 1
Reviewer: 1

Output:
Basic reporting: Please see the attached file.
Experimental design: Please see the attached file.
Validity of the findings: Please see the attached file.
Additional comments: Please see the attached file.


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: SEGMENTATION OF MULTI-TEMPORAL POLARIMETRIC SAR DATA BASED ON MEAN-SHIFT AND SPECTRAL GRAPH PARTITIONING
Review round: 1
Reviewer: 2

Output:
Basic reporting: no comment
Experimental design: no comment
Validity of the findings: no comment
Additional comments: The article is good and well explained. A new algorithm for multi-temporal PolSAR image segmentation is proposed in this paper. It could be useful to solve the segmentation problem in some specific difficult scenes, e.g. cropland, where crops of different types and different sowing times are easy to show similar characteristics on single-temporal PolSAR images.

1.	Line 297: More details in preprocessing steps should be given, such as window sizes, geographical coordinate system, software.
2.	Line: 304: How to set the minimum segmentation region parameter M? The value of M (192) in the third date is different from values (235) in another two dates. What is the reason?
3.	Line 339: The number of segmentation regions is set to 47. However, it can be seen from Figure 15 that the segmentation accuracy reached a peak at 50 and stabilized in the range of 40-120. Why don’t you choose 50 as the number of segmentation?
4.	Line 386-388: The specific parameter setting should firstly ensure the realization of over-segmentation, and secondly consider the influence of the number of regions on the operation cost. How to set the specific parameter in practice. Could you give more details?
5.	It is better to show the correct segmentation map with bright colors in Figures 14 and 19. In addition, the segmentation accuracy should be given in Figure 14.
6.	The current discussion part presents segmentation accuracies with single-temporal PolSAR images and different temporal combinations. It is more like the result part. In the discussion part, the authors could discuss what are their specific research findings or some influence factors. Also, the relation of this study to previous studies to show its significance is high will be more convincing and it is recommended.


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: SEGMENTATION OF MULTI-TEMPORAL POLARIMETRIC SAR DATA BASED ON MEAN-SHIFT AND SPECTRAL GRAPH PARTITIONING
Review round: 2
Reviewer: 1

Output:
Basic reporting: The reviewer does not have further comments.
Experimental design: The reviewer does not have further comments.
Validity of the findings: The reviewer does not have further comments.
Additional comments: The reviewer does not have 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: SEGMENTATION OF MULTI-TEMPORAL POLARIMETRIC SAR DATA BASED ON MEAN-SHIFT AND SPECTRAL GRAPH PARTITIONING
Review round: 2
Reviewer: 2

Output:
Basic reporting: no comment
Experimental design: no comment
Validity of the findings: no comment
Additional comments: The authors have made proper revisions. I have no other 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 SURVEY OF CRYPTOSPORIDIUM PREVALENCE AMONG BIRDS IN TWO ZOOS IN CHINA
Review round: 1
Reviewer: 1

Output:
Basic reporting: In the present paper, authors collected 263 fecal samples from 43 avian species from zoos. C. parvum was detected by sequencing the 18S rRNA gene of Cryptosporidium. The paper is well organized and generally well written, though there are a few minor errors like grammar and structure throughout the manuscript.
Experimental design: no problems
Validity of the findings: The results demonstrate flamingo and white crane infection by C. parvum for the first time. The results of our study provide an important reference for understanding the host range, biological characteristics, and molecular epidemiology of C. parvum.
Additional comments: Line 40, 45 and 139, it would be better to write the scientific name of the hosts after the common name. I do not find white crane and flamingo in Table S1. There were sever papers that have reported Cryptosporidium in crane. The Table should add common names

Line 50-52, please rewrite “Cryptosporidium is prevalent in fish, amphibians……”.

Line 66-68, C. parvum is Cryptosporidium species, not disease. “…is also prevalent in avian” means what? avian intestine? Please rewrite this sentence.

Line 71-76, “wild birds such as Canada goose, mallard, coot……” this sentence is not complete. Please rewrite.

Line 78-93, the language and structure are so poor. Authors need to rewrite these sentences.

Line 82, does the author have any reference to refer to, if so please add.

Line 95, how did the author collect the samples, please add them.

Line107-117, whether the primer sequence refers to other articles?

Please add Statistical analysis, I think you used "Descriptive analysis (percentages)", as well. So, you should add the sentence.

Please explain, how to protect contamination during the stool collection and collect the stools from the same bird.

Why the author did not perform subtype analysis of positive samples

I find that the sequence uploaded by the author did have several base differences with the standard sequence. Did the author analyzed the cause, whether it could be sequencing problems or other causes of the problem?

Line172-174, how can the author come to this conclusion with few data? please clarify.

Why did the authors choose Brazil and Ireland for data 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: A SURVEY OF CRYPTOSPORIDIUM PREVALENCE AMONG BIRDS IN TWO ZOOS IN CHINA
Review round: 1
Reviewer: 2

Output:
Basic reporting: The paper presents that the total infection rate of Cryptosporidium in birds in Beijing and Harbin zoos is 1.9%, and it was found that white cranes and flamingos were infected with C. parvum for the first time. By analyzing the gene flow of C. parvum in birds and other animals, it is concluded that bird C. parvum has the risk of spilling to humans and other mammals. However, the paper needs significant improvement before acceptance for publication.
Experimental design: The first discovery of C. parvum infection in white cranes and flamingos and the analysis of gene flow of C. parvum in different hosts are the two highlights of this paper. These research results are conducive to the prevention and control of bird Cryptosporidium in zoos in the future.
    The 18S rRNA gene method used in the paper works very well for the prevalence, phylogeny and genetic evolution of Cryptosporidium, this method is a well-established method, on this basis, the gene flow of C. parvum in different hosts was analyzed by biological software.
Validity of the findings: The results of this study are credible, but the description of the results is not detailed enough. For example, at lines 159-167 only list the data but do not make a detailed analysis. It is suggested that you should supplement the description of the results to increase its integrity.
Additional comments: The conclusions presented in this paper are inaccurate and rigorous. For example, it is proposed in the conclusion that C. parvum infection is found in white cranes and flamingos for the first time, but the specific location is not specified. Is this the first time in China or the first time in the world. It is hoped that you will re summarize to draw a correct and unambiguous conclusion.
      The English language should be improved to ensure that an international audience can clearly understand your text. It is noted that your manuscript needs careful editing by someone with expertise in technical English editing paying particular attention to English grammar, spelling, and sentence structure so that the goals and results of the study are clear to the reader.
     Figures and tables should be annotated in more detail. Whether “Table 5” on the last page should be “Table 3”？


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: BIOINFORMATICS ANALYSIS AND IDENTIFICATION OF HUB GENES AND IMMUNE-RELATED MOLECULAR MECHANISMS IN CHRONIC MYELOID LEUKEMIA
Review round: 1
Reviewer: 1

Output:
Basic reporting: no comment
Experimental design: no comment
Validity of the findings: no comment
Additional comments: Manuscript Title: “Bioinformatics analysis and identification of hub genes and immune-related molecular mechanisms in chronic myeloid leukemia”
Summarizing the main findings of the study:
Fangyi Yao al. used the GSE100026 datasets、ImmPort database and MSigDB database to identify the DEGs from Chronic myeloid leukemia (CML). Since, the CML has a significant related to immune, authors aimed to identify immune-related hub genes, pathways, and the expression profiles using an integrative bioinformatics analysis. Also, authors have utilized various bioinformatic pipelines to analyse the datasets such as R software package, Cytoscape, KEGG. DEGs were separately analyzed by Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) with Metascape database, the protein–protein interaction (PPI) network of the DEGs was analyzed by STRING and visualized in Cytoscape, 10 key genes from PPI network by MCODE plug-ins. Furthmore ,GSEA to get the related pathway and CIBERSORT is used to evaluate the composition of immune cells and so on . in the end of the aticle, the writer clollected serum of patients to test the hub gene expression by qRT-PCR.

I would recommend the manuscript to be accepted with minor revisions.
Minor concerns:
1.	Firstly, authors are requested to provide the workflow .using brief word to describe your article structure in the introduction.
2.	The figure 9 is unclearly that can not explian the result,please review .
3.	The method is not be provied about “Correlation analysis hub gene “. Please review it and explian how to get annlysis hub gene expression of corralation in three databases.
4.	Please provied the patients clinicopathological.and get the correlation between the hub gene expression and clinicopathologica.


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: BIOINFORMATICS ANALYSIS AND IDENTIFICATION OF HUB GENES AND IMMUNE-RELATED MOLECULAR MECHANISMS IN CHRONIC MYELOID LEUKEMIA
Review round: 1
Reviewer: 2

Output:
Basic reporting: 1. In line 53 and 54, the authors cited only 2021 references in their introduction of the features of CML. However, these features of CML should have been discovered earlier to 2021. Please citing the references correctly and to check other references in this study.

2. The full name was not provided when the abbreviation first appeared, such as line 30, 43 and 44. It is recommended to modify and review the full text again.
Experimental design: 1. In the part of Validating hub genes expression in clinical samples (line 210), the authors only provided the q-PCR results of the healthy donors and CML patients, but did not provide the relevant clinical information, such as the age and sex of the healthy donors and CML patients, the routine blood test and diagnosis of the CML patients. Because age, gender and presence of infection may affect the expression of immune-related genes. So, I think it is necessary for the authors to provide these information and detail the age and sex matching between healthy donors and CML patients.

2. The description of the part of GESA analysis of hub genes (line 186), Hub genes for CML diagnosis (line 194), Immune infiltration analysis (line 199), Correlation analysis between diagnostic markers and immune cells (line 204) and Validating hub genes expression in clinical samples (line 210) were too simple that the authors only showed the figures. It is better to add a detailed description of the results, in order to facilitate more readers’ understanding of this study.

3. In line 95, the authors find the IRGs by using the intersection of the differentially expressed genes and the immune genes. What is the immune genes? A database or others research?

4. In line 110, the authors retained the genes with an AUC value greater than 0.7. Why selected 0.7 and is it supported by the literature?
Validity of the findings: 1. In line 209, “This indicated that immunity was poor.” But I could not find more description or evidence to support this conclusion. So, I suggest the authors to add a detailed description to illustrate it 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: BIOINFORMATICS ANALYSIS AND IDENTIFICATION OF HUB GENES AND IMMUNE-RELATED MOLECULAR MECHANISMS IN CHRONIC MYELOID LEUKEMIA
Review round: 1
Reviewer: 3

Output:
Basic reporting: This manuscript is well-written in general.

1)	The writings on the plots of Figure 3b and Figure 3d are not visible. It is better to increase the text size.
2)	“et al.” should be written in italic.
3)	The primer sequences under the heading “RNA isolation and quantitative real-time PCR (RT-qPCR)” (lines 144 - 153) are better to be given as a table.
4)	Gene names should be written in italic (lines 183 - 184, 205 - 206, 211).
5)	It is better to use “the efficacy of CML treatment” instead of “the efficacy of treatment of CML” (line 219).
6)	The sentence in lines 241 – 242 should be changed as “Their expressions were significantly associated with a variety of immune cell disorders by immune infiltration analysis.”.
7)	“in vivo.” should be written italic (line 258).
8)	BCR-ABL1 is also mentioned as BCR/ABL or BCR-ABL in different paragraphs of the manuscript. They all should be corrected as BCR-ABL1.
Experimental design: It is regarding CML is informative for the readers. Experiments are well defined and the results are meaningful. Bioinformatics analysis is dealt with in detail.
Validity of the findings: Even though the patient samples were limited, the findings seem valuable. If supported with further experiments novel marker or therapeutic target candidates may be defined for CML. The paper is scientifically adequate.
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: BIOINFORMATICS ANALYSIS AND IDENTIFICATION OF HUB GENES AND IMMUNE-RELATED MOLECULAR MECHANISMS IN CHRONIC MYELOID LEUKEMIA
Review round: 2
Reviewer: 1

Output:
Basic reporting: No comment
Experimental design: No comment
Validity of the findings: No comment
Additional comments: In line 236-237, “ T cellscells CD8, and T cells CD4 naive” The description of T cell subsets does not seem to conform to the conventional description. It is generally described as CD8+ T cells, CD4+ T cells. So, I suggested that the authors revise it and check the full manuscript.


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: BIOINFORMATICS ANALYSIS AND IDENTIFICATION OF HUB GENES AND IMMUNE-RELATED MOLECULAR MECHANISMS IN CHRONIC MYELOID LEUKEMIA
Review round: 2
Reviewer: 2

Output:
Basic reporting: The revision looks good.
Experimental design: The revision looks good.
Validity of the findings: The revision looks good.
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: EXPLORING THE NITROGEN RESERVOIR OF BIODEGRADABLE HOUSEHOLD GARBAGE AND ITS POTENTIAL IN REPLACING SYNTHETIC NITROGEN FERTILIZERS IN CHINA
Review round: 1
Reviewer: 1

Output:
Basic reporting: pass
Experimental design: pass
Validity of the findings: pass
Additional comments: This manuscript did statistical analysis the biodegradable household garbage resources and their nitrogen reservoirs in China. It’s great valuable dataset for the national source assessment. However, several key parameters are unclear or need provide in the text.
1.	The text looks a data investigation. I suggested authors compare the results in China to other countries.
2.	I suggested authors separate provinces to seven groups, e.g., north, south, east, central northwest, northeast, southwest of China and provided the per capita biodegradable household garbage resources in these seven regions.
3.	I suggested authors provide the urban increase and rural decrease yearly rates of food waste, waste paper, wood chips and biodegradable household garbage among the study period. If it’s possible, these yearly rates can detail to seven regions. It can list in a Table.
4.	L26-28, It’s not concluded from your result. I suggested author removed it from abstract.
5.	L51-53, this sentence told us that biodegradable household garbage resources in China has reported several years ago. Why you reported it again? It should point out the different or novel to previous studies.
6.	L75-76, It is conflict to L 51-53.
7.	L95-96, The potential reasons for except these three regions should be point out.
8.	L219-L220, This result is slight less than the data from Wu et al, 2018. What are the potential reasons?
9.	The formula between GDP and food wastes should be showed in figure 5.


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: EXPLORING THE NITROGEN RESERVOIR OF BIODEGRADABLE HOUSEHOLD GARBAGE AND ITS POTENTIAL IN REPLACING SYNTHETIC NITROGEN FERTILIZERS IN CHINA
Review round: 1
Reviewer: 2

Output:
Basic reporting: This manuscript presents an interesting summary of the nitrogen reservoir of biodegradable household garbage in China, and further assesses the potential in replacing synthetic nitrogen fertilizers, by collecting the original data from multi-channel. This work is within the scope of the journal and the quality of the article is also well written. It can be considered to publish after moderate revision.
Experimental design: See detailed comments.
Validity of the findings: See detailed comments.
Additional comments: Detailed comments are as follows:
1.	In abstract, the description of the research background and method is too much, even accounts for half of the abstract (Line 17-23). Moreover, the more presentation of specific key data in abstract is necessary (e.g., the temporal variations of the calculation results).
2.	Line 51: “2.01 billion t a-1” should be “2.01×10^9 t a-1” (be consistent with the abstract). The presentation of data needs to be unified.
3.	Line 58. The authors mentioned that “Nitrogen, an essential nutrient for plants growth, is the key element in the agricultural ecosystem”. Obviously, it is better to mention that areas with poor soil need more exogenous nitrogen as an essential nutrient, the two references below can support this.
https://doi.org/10.1016/j.agee.2020.106883
https://doi.org/10.1016/j.agee.2020.107027
4.	Introduction: The authors mentioned briefly that nitrogen reservoir of the biodegradable components of household garbage in a whole country is not clear. Does this mean that the research topic of this paper is a completely new field? Maybe rarely reported in China, what about the other countries？It is recommended that the publications of this unique “nitrogen reservoir” be appropriately summarized and added to the introduction (perhaps a short paragraph).
5.	Methods: An significant concern. How does the author make statistical calculations on the collected data from the China Statistical Yearbook, Web of Science, CNKI? These publications may provide a series of data, such as the total output of urban and rural food waste each year. What is the spatial scale of these data? Provincial scale or City scale？Whether the authors took the mean values of these data to calculate in section 2.2, 2.3, ……  If the average values were selected, whether the data set has been tested for normal distribution？In the case of non-normal distribution, the average value is not suitable for calculating and reflecting the overall level, while the median value may be more suitable.
6.	Section 3.5: The significant linear positive correlation between the GDP and the amount of food wastes of different provinces of China seems not very suitable here. How about the relationship between per capital GDP and the per capital discharge of food waste？
7.	Discussion: It would be better to discuss more about the spatial scale differences of the potential of biodegradable household garbage of replacing synthetic nitrogen fertilizers.


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: EXPLORING THE NITROGEN RESERVOIR OF BIODEGRADABLE HOUSEHOLD GARBAGE AND ITS POTENTIAL IN REPLACING SYNTHETIC NITROGEN FERTILIZERS IN CHINA
Review round: 2
Reviewer: 1

Output:
Basic reporting: See additional comments
Experimental design: See additional comments
Validity of the findings: See additional comments
Additional comments: The authors responded to reviewers' concerns in a reasonable way. The manuscript can be accepted in present form.


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: PREDICTION OF ACTIVE INGREDIENTS IN SALVIA MILTIORRHIZA BUNGE. BASED ON SOIL ELEMENTS AND ARTIFICIAL NEURAL NETWORK
Review round: 1
Reviewer: 1

Output:
Basic reporting: no comment
Experimental design: no comment
Validity of the findings: no comment
Additional comments: 1. The results were mainly obtained by the method of the artificial neural network, thus the description of the data should be more conservative throughout the manuscript.
2. The quality of figure 1 should be improved.
3. A conclusive or abstract graph will be helpful for the general readers.