size_categories:n<1K format:parquet modality:tabular modality:text library:datasets library:pandas library:mlcroissant library:polars library:distilabel region:us synthetic distilabel rlaif
---
size_categories: n<1K
dataset_info:
  features:
  - name: text
    dtype: string
  - name: id
    dtype: string
  - name: dump
    dtype: string
  - name: url
    dtype: string
  - name: file_path
    dtype: string
  - name: language
    dtype: string
  - name: language_score
    dtype: float64
  - name: token_count
    dtype: int64
  - name: score
    dtype: float64
  - name: int_score
    dtype: int64
  - name: system_prompt
    dtype: string
  - name: conversation
    list:
    - name: content
      dtype: string
    - name: role
      dtype: string
  - name: gen_conv_model_name
    dtype: string
  - name: generations
    sequence: string
  - name: distilabel_metadata
    struct:
    - name: raw_output_chat_generation_2
      dtype: string
  - name: generations_model_names
    sequence: string
  splits:
  - name: train
    num_bytes: 2759930
    num_examples: 100
  download_size: 1147408
  dataset_size: 2759930
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
tags:
- synthetic
- distilabel
- rlaif
---

<p align="left">
  <a href="https://github.com/argilla-io/distilabel">
    <img src="https://raw.githubusercontent.com/argilla-io/distilabel/main/docs/assets/distilabel-badge-light.png" alt="Built with Distilabel" width="200" height="32"/>
  </a>
</p>

# Dataset Card for fine-preferences-magpie-v6-tasky-7-3

This dataset has been created with [distilabel](https://distilabel.argilla.io/).



## Dataset Summary

This dataset contains a `pipeline.yaml` which can be used to reproduce the pipeline that generated it in distilabel using the `distilabel` CLI:

```console
distilabel pipeline run --config "https://huggingface.co/datasets/distilabel-internal-testing/fine-preferences-magpie-v6-tasky-7-3/raw/main/pipeline.yaml"
```

or explore the configuration:

```console
distilabel pipeline info --config "https://huggingface.co/datasets/distilabel-internal-testing/fine-preferences-magpie-v6-tasky-7-3/raw/main/pipeline.yaml"
```

## Dataset structure

The examples have the following structure per configuration:


<details><summary> Configuration: default </summary><hr>

```json
{
    "conversation": [
        {
            "content": "Design a strategy to create giant shells in the interstellar medium of spiral galaxies, leveraging the energy released by Gamma Ray Bursts (GRBs).",
            "role": "user"
        },
        {
            "content": "To create giant shells in the interstellar medium (ISM) of spiral galaxies, leveraging the energy released by Gamma Ray Bursts (GRBs), I propose a multi-step strategy:\n\n1. **GRB Energy Deposition**: Identify a suitable GRB event with an energy output of approximately 10^53 ergs, which is sufficient to create a kpc-size shell in the ISM. The GRB\u0027s energy will heat the local gas to above 10^7 K, creating a high-pressure bubble.\n\n2. **Initial Expansion Phase**: During the initial expansion phase, the bubble will expand rapidly, driven by the high pressure and temperature. This phase will last for approximately 10^4 to 10^5 years, depending on the energy output and the density of the surrounding ISM.\n\n3. **Pressurized Expansion Phase**: As the bubble expands, it will enter a pressurized expansion phase, where the pressure inside the bubble is higher than the surrounding ISM. This phase will last for approximately 10^5 to 10^6 years. During this phase, the bubble will continue to expand, and the momentum acquired will be sufficient to snowplow the surrounding ISM, creating a giant shell.\n\n4. **Disk Blowout**: As the bubble expands, it will eventually break out of the galactic disk, leading to disk blowout. This will result in a significant loss of energy, but the momentum acquired during the pressurized expansion phase will ensure that the bubble continues to expand and create a giant shell.\n\n5. **Shell Formation and Evolution**: The giant shell will continue to evolve, driven by the remaining energy and momentum. The shell\u0027s size and shape will be influenced by the surrounding ISM density, magnetic fields, and other environmental factors.\n\n6. **GRB Remnant Identification**: After the shell has formed, identify the GRB remnant, which may be difficult to detect due to its age. The remnant could be an old star cluster or a faint, diffuse source.\n\n**Key Considerations**:\n\n* The frequency of GRBs in normal galaxies should be sufficient to account for the number of observed giant shells.\n* The energy output of the GRB should be sufficient to create a kpc-size shell, but not so high that it disrupts the entire galaxy.\n* The surrounding ISM density and environmental factors will influence the shell\u0027s size, shape, and evolution.\n* The strategy should be adaptable to different galaxy types and environments.\n\n**Potential Challenges and Limitations**:\n\n* Radi",
            "role": "assistant"
        },
        {
            "content": "How would you contrast the approach described in the document with the standard model for the origin of giant shells in spiral galaxies, which involves multiple supernovae?",
            "role": "user"
        },
        {
            "content": "The approach described in the document, which leverages the energy released by Gamma Ray Bursts (GRBs) to create giant shells in the interstellar medium (ISM) of spiral galaxies, differs significantly from the standard model for the origin of giant shells, which involves multiple supernovae. Here are the key contrasts:\n\n**Energy Source**:\n\n* GRB-driven model: A single, extremely energetic event (GRB) releases a massive amount of energy (10^53 ergs) to create the giant shell.\n* Standard model: Multiple supernovae, each releasing a smaller amount of energy (10^51 ergs), cumulatively contribute to the formation of the giant shell.\n\n**Timescale**:\n\n* GRB-driven model: The energy deposition and initial expansion phase occur on a very short timescale (10^4 to 10^5 years), followed by a longer pressurized expansion phase (10^5 to 10^6 years).\n* Standard model: The supernovae explosions occur over a longer period, potentially spanning millions of years, with each event contributing to the gradual formation of the giant shell.\n\n**ISM Disruption**:\n\n* GRB-driven model: The GRB\u0027s energy heats the local gas to extremely high temperatures (above 10^7 K), creating a high-pressure bubble that rapidly expands and disrupts the surrounding ISM.\n* Standard model: Multiple supernovae explosions create a series of smaller, overlapping bubbles that gradually carve out the giant shell, with less intense disruption of the surrounding ISM.\n\n**Shell Formation**:\n\n* GRB-driven model: The giant shell forms primarily due to the momentum acquired during the pressurized expansion phase, which snowplows the surrounding ISM.\n* Standard model: The giant shell forms through the cumulative effect of multiple supernovae explosions, which create a series of cavities and shells that eventually merge to form a larger structure.\n\n**Challenges and Limitations**:\n\n* GRB-driven model: The frequency of GRBs in normal galaxies might be insufficient to account for the number of observed giant shells. Additionally, the energy output of the GRB must be carefully calibrated to create a shell of the desired size.\n* Standard model: The model faces challenges related to radiative cooling, evaporative losses, and disk blowout, which can reduce the effectiveness of the supernovae in creating and maintaining the giant shell.\n\nIn summary, the GRB-driven model proposes a more rapid and energetic process, driven by a single event, whereas the standard model",
            "role": "assistant"
        },
        {
            "content": "Analyze the document\u0027s main argument from the perspective of a specific stakeholder group, such as astronomers, policymakers, or the general public.",
            "role": "user"
        }
    ],
    "distilabel_metadata": {
        "raw_output_chat_generation_2": "I\u0027ll analyze the document\u0027s main argument from the perspective of astronomers.\n\n**Astronomers\u0027 Perspective**\n\nAs astronomers, our primary concern is the scientific validity and implications of the proposed model. Here\u0027s our analysis:\n\n**Strengths:**\n\n1. **Novelty and Innovation**: The idea of leveraging GRBs to create giant shells in spiral galaxies is a fresh and intriguing concept. It challenges our current understanding of galaxy evolution and offers a new avenue for research.\n2. **Energetic Constraints**: The document\u0027s emphasis on the enormous energy output of GRBs (10^53 ergs) is a strong point. It\u0027s well-established that GRBs are among the most energetic events in the universe, making them a plausible driver for shaping galaxy morphology.\n3. **Cosmological Significance**: If confirmed, this model could have significant implications for our understanding of galaxy evolution, particularly in the context of high-redshift galaxies where GRBs are more frequent.\n\n**Weaknesses and Concerns:**\n\n1. **Lack of Observational Evidence**: Currently, there is no direct observational evidence to support the claim that GRBs create giant shells in spiral galaxies. Astronomers would need to see convincing data and correlations between GRB events and shell formation.\n2. **Theoretical Uncertainties**: The document\u0027s discussion of the Pressurized Expansion Phase and Disk Blowout is largely theoretical and lacks concrete simulations or modeling. Astronomers would need to see more detailed, rigorous calculations to support these claims.\n3. **Alternative Explanations**: The standard model, involving multiple supernovae, is well-established and has been supported by numerous observations. Astronomers would need to see compelling arguments and evidence to abandon this model in favor of the GRB-driven approach.\n4. **GRB Frequency and Distribution**: The frequency and distribution of GRBs in normal galaxies might not be sufficient to account for the number of observed giant shells. Astronomers would need to see a more detailed analysis of GRB demographics and their potential impact on galaxy evolution.\n\n**Conclusion**\n\nFrom an astronomical perspective, the document\u0027s main argument is intriguing but requires further development and evidence to be convincing. While the idea of GRBs shaping galaxy morphology is novel and worth exploring, astronomers would need to see more rigorous theoretical work, simulations, and observational evidence to support this claim. The standard model, involving multiple supernovae, remains a well-established and well-supported explanation for giant shell formation, and significant evidence would be required to supplant it."
    },
    "dump": "CC-MAIN-2013-20",
    "file_path": "s3://commoncrawl/crawl-data/CC-MAIN-2013-20/segments/1368696381249/warc/CC-MAIN-20130516092621-00000-ip-10-60-113-184.ec2.internal.warc.gz",
    "gen_conv_model_name": "meta-llama/Meta-Llama-3-70B-Instruct",
    "generations": [
        " From the perspective of the general public, the main argument in the document proposing a strategy to create giant shells in the interstellar medium (ISM) of spiral galaxies using Gamma Ray Bursts (GRBs) presents a captivating vision of astrophysics and cosmic phenomena. The primary stakeholders in this context are citizens who, while not directly involved in research or policy-making, have a general curiosity and interest in space exploration and the understanding of the universe.\n\nThe document highlights the potential of harnessing the colossal energy from GRBs to create vast, intricate structures in the ISM, demonstrating the immense power and scale of these events. This imaginative proposal might inspire the public\u0027s fascination with the universe and its underlying mechanics, leading to increased support for space research and exploration.\n\nMoreover, the document\u0027s focus on a specific mechanism for creating giant shells can spark curiosity about the broader field of astrophysics. The general public may become intrigued by questions such as, \"How do galaxies form and evolve?\", \"What processes govern the structure and composition of the ISM?\", and \"What role do extreme events like GRBs play in the universe\u0027s development?\"\n\nTo further capitalize on public interest, educational outreach programs can be designed to engage students and the general public. These programs can help people understand the science behind the proposal, the importance of studying astrophysics, and the potential implications of the research.\n\nHowever, it\u0027s crucial to emphasize that the proposal is speculative and not yet supported by empirical evidence. This distinction should be made clear to avoid misconceptions or overhyping the idea. The document can be used as a conversation starter to foster curiosity and inspire interest in astrophysics, rather than a definitive plan for creating giant shells in spiral galaxies.",
        "From the perspective of astronomers, the main argument of the document presents a novel and potentially groundbreaking approach to understanding the formation of giant shells in spiral galaxies. The proposed GRB-driven model offers an alternative to the current understanding, which relies on multiple supernovae. By leveraging the energy released by a single, extremely powerful event, the model offers a more efficient and rapid means of creating giant shells in the interstellar medium.\n\nFor astronomers, the GRB-driven model offers several exciting prospects for future research and exploration:\n\n1. **Expanding the Understanding of Gamma Ray Bursts**: GRBs are among the most energetic events in the Universe, yet their impact on their host galaxies remains poorly understood. The proposed model provides a new context for studying the role of GRBs in shaping the structure and evolution of spiral galaxies.\n\n2. **Testing the Model\u0027s Predictions**: The GRB-driven model makes specific predictions about the size, shape, and evolution of giant shells, which can be tested through observational studies and numerical simulations. By comparing the model\u0027s predictions to real-world observations, astronomers can refine and validate the model, or identify areas where it needs to be modified or expanded.\n\n3. **Exploring the Connection Between GRBs and Galaxy Evolution**: The GRB-driven model suggests a direct link between the most energetic events in the Universe and the large-scale structure of galaxies. By investigating this connection, astronomers can gain new insights into the role of extreme events in shaping the evolution of galaxies over cosmic time.\n\n4. **Improving the Understanding of the ISM**: The GRB-driven model offers a unique opportunity to study the properties and behavior of the interstellar medium in spiral galaxies. By analyzing the formation and evolution of giant shells, astronomers can gain new insights into the physical processes that govern the ISM, such as turbulence, magnetic fields, and radiative cooling.\n\nIn conclusion, the GRB-driven model provides a fascinating and potentially transformative perspective on the formation of giant shells in spiral galaxies. For astronomers, the model offers a wealth of opportunities for exploration, discovery, and understanding of the Universe\u0027s most energetic events and their role in shaping its large-scale structure.",
        "I\u0027ll analyze the document\u0027s main argument from the perspective of astronomers.\n\n**Astronomers\u0027 Perspective**\n\nAs astronomers, our primary concern is the scientific validity and implications of the proposed model. Here\u0027s our analysis:\n\n**Strengths:**\n\n1. **Novelty and Innovation**: The idea of leveraging GRBs to create giant shells in spiral galaxies is a fresh and intriguing concept. It challenges our current understanding of galaxy evolution and offers a new avenue for research.\n2. **Energetic Constraints**: The document\u0027s emphasis on the enormous energy output of GRBs (10^53 ergs) is a strong point. It\u0027s well-established that GRBs are among the most energetic events in the universe, making them a plausible driver for shaping galaxy morphology.\n3. **Cosmological Significance**: If confirmed, this model could have significant implications for our understanding of galaxy evolution, particularly in the context of high-redshift galaxies where GRBs are more frequent.\n\n**Weaknesses and Concerns:**\n\n1. **Lack of Observational Evidence**: Currently, there is no direct observational evidence to support the claim that GRBs create giant shells in spiral galaxies. Astronomers would need to see convincing data and correlations between GRB events and shell formation.\n2. **Theoretical Uncertainties**: The document\u0027s discussion of the Pressurized Expansion Phase and Disk Blowout is largely theoretical and lacks concrete simulations or modeling. Astronomers would need to see more detailed, rigorous calculations to support these claims.\n3. **Alternative Explanations**: The standard model, involving multiple supernovae, is well-established and has been supported by numerous observations. Astronomers would need to see compelling arguments and evidence to abandon this model in favor of the GRB-driven approach.\n4. **GRB Frequency and Distribution**: The frequency and distribution of GRBs in normal galaxies might not be sufficient to account for the number of observed giant shells. Astronomers would need to see a more detailed analysis of GRB demographics and their potential impact on galaxy evolution.\n\n**Conclusion**\n\nFrom an astronomical perspective, the document\u0027s main argument is intriguing but requires further development and evidence to be convincing. While the idea of GRBs shaping galaxy morphology is novel and worth exploring, astronomers would need to see more rigorous theoretical work, simulations, and observational evidence to support this claim. The standard model, involving multiple supernovae, remains a well-established and well-supported explanation for giant shell formation, and significant evidence would be required to supplant it."
    ],
    "generations_model_names": [
        "mistralai/Mixtral-8x7B-Instruct-v0.1",
        "NousResearch/Nous-Hermes-2-Mixtral-8x7B-DPO",
        "meta-llama/Meta-Llama-3-70B-Instruct"
    ],
    "id": "\u003curn:uuid:e2300ad5-01dd-4e80-92b3-7ec88785cc9d\u003e",
    "int_score": 3,
    "language": "en",
    "language_score": 0.9126408100128174,
    "score": 2.765625,
    "system_prompt": "\nYou\u0027re a helpful AI assistant that responds to complex user tasks based on a document\u0027s content, without explicitly mentioning the document. \nFollow these guidelines:\n\n## 1. Preparation\n\n- Thoroughly analyze the document\u0027s main topics, key points, themes, and any data or methodologies presented.\n- The interaction will consist of complex user tasks, follow-up questions, and detailed AI assistant responses.\n\n## 2. Interaction Structure and Roles\n\nThis interaction involves two roles: the User and the AI Assistant. The conversation will follow this structure:\n\n1. User: Provides complex tasks and follow-up questions.\n   First message format: \u003ctask_description\u003e\n   Subsequent messages:\n   a) \u003cquestion_or_comment\u003e\n   b) \u003cnew_task_description\u003e\n\n2. AI Assistant: Responds to tasks and follow-up questions using information from the document.\n\nThe conversation will follow this pattern:\n[TASK] -\u003e AI Response -\u003e [FOLLOW-UP] -\u003e AI Response -\u003e [FOLLOW-UP] -\u003e AI Response -\u003e [NEXT TASK] -\u003e AI Response -\u003e (repeat)\n\nUser Guidelines:\n- The first message MUST be a complex task related to the document\u0027s content.\n- For [FOLLOW-UP], ask for clarification, request examples, challenge the AI\u0027s response, or propose alternatives.\n- Use [NEXT TASK] to introduce a new complex task exploring a different aspect of the document.\n\nAI Assistant Guidelines:\n- Provide detailed responses to tasks and thoughtful engagement with follow-ups.\n- Never mention or reference the source document directly.\n\n## 3. User Task Characteristics\n\nComplex tasks should:\n\n- Challenge various cognitive skills, including but not limited to:\n  * Analysis and critical thinking\n  * Synthesis of ideas\n  * Evaluation and assessment\n  * Creative problem-solving\n  * Application of concepts to new contexts\n  * Predictive reasoning\n  * Comparative analysis\n\n- Require multi-step thinking or consideration of multiple factors\n- Encourage exploration of different perspectives or stakeholders\n- Prompt the application of document content to real-world scenarios\n- Involve interdisciplinary connections where applicable\n- Stimulate innovative thinking and novel applications of ideas\n- Address potential challenges, limitations, or ethical considerations\n- Encourage the development of actionable strategies or solutions\n\nVary the scope and nature of tasks, alternating between broad, overarching challenges and more focused, specific problems. Adapt the complexity and technical depth of tasks to match the document\u0027s content and intended audience.\n\nAvoid simple, fact-based questions or tasks that can be completed with surface-level understanding. Instead, craft tasks that necessitate a thorough comprehension and creative application of the document\u0027s key concepts, methodologies, or findings.\n\n### Enhanced Task Variety\n\nTo ensure a wide variety of complex opening tasks, consider the following approaches:\n\n1. Hypothetical Scenarios: \"Imagine a world where [key concept from the document] is reversed. How would this impact [related systems or processes]?\"\n\n2. Comparative Analysis: \"Contrast the approach described in the document with [alternative approach]. What are the strengths and weaknesses of each?\"\n\n3. Ethical Dilemmas: \"Present an ethical dilemma that arises from implementing the ideas in the document. How would you navigate this challenge?\"\n\n4. Interdisciplinary Integration: \"Propose a way to integrate the document\u0027s core concepts with [unrelated field]. What novel applications could emerge?\"\n\n5. Historical Context: \"Trace the evolution of [key idea] discussed in the document. How might it continue to evolve in the next decade?\"\n\n6. Stakeholder Perspectives: \"Analyze the document\u0027s main argument from the perspective of [specific stakeholder group]. What concerns or opportunities would they identify?\"\n\n7. Systems Thinking: \"Map out the systemic implications of implementing the document\u0027s central proposal. Include both intended and potential unintended consequences.\"\n\n8. Future Forecasting: \"Based on the trends discussed in the document, predict three possible scenarios for [related area] in 20 years. What factors would influence each outcome?\"\n\n9. Resource Allocation: \"Design a strategy to implement the document\u0027s key recommendations with limited resources. What trade-offs would you make and why?\"\n\n10. Cross-Cultural Application: \"Evaluate how the document\u0027s findings might be applied in [specific cultural context]. What adaptations would be necessary?\"\n\n11. Risk Assessment: \"Conduct a comprehensive risk analysis of the primary method or theory presented in the document. How could these risks be mitigated?\"\n\n12. Innovation Challenge: \"Propose three unconventional ways to apply the document\u0027s central concept in [unrelated industry]. How might these innovations disrupt the status quo?\"\n\n13. Policy Formulation: \"Draft a policy framework based on the document\u0027s insights. Address potential opposition and implementation challenges.\"\n\n14. Competitive Analysis: \"Position the document\u0027s main idea as a market offering. How would it compete against existing solutions, and what would be its unique value proposition?\"\n\n15. Paradigm Shift: \"Argue for or against the notion that the document\u0027s central thesis represents a paradigm shift in its field. Support your position with evidence and reasoning.\"\n\n## 4. AI Assistant Characteristics\n\n- Provide comprehensive, well-structured responses that directly address all aspects of the complex task.\n- Draw connections between different parts of the document to create a cohesive analysis or solution.\n- Offer concrete examples, potential scenarios, or case studies to illustrate your points when appropriate.\n- Be prepared to break down complex tasks into manageable steps or components in your response.\n\n## 5. Engagement\n\n- Maintain a professional and analytical tone throughout the interaction.\n- Encourage critical thinking by highlighting potential challenges or alternative viewpoints in your responses.\n- Conclude complex tasks with a summary of key points or next steps when appropriate.\n\n## 6. General Guidelines\n\n- Ensure the interaction demonstrates a high level of expertise and in-depth understanding of the document\u0027s content.\n- The AI\u0027s knowledge should reflect the document\u0027s scope but also show the ability to apply this information to novel situations or problems.\n- Adapt the level of detail and technical language to match the complexity of the user\u0027s task.\n\nRemember: Never mention or directly reference the source document in the generated interaction. The AI assistant should present information and analysis as if it\u0027s part of its general knowledge base and problem-solving capabilities.\n\n## Document\n\nPrevious abstract Next abstract\nSession 40 - The Interstellar Medium.\nDisplay session, Tuesday, June 09\nGamma Ray Burst (GRB) explosions can make kpc-size shells and holes in the interstellar media (ISM) of spiral galaxies if much of the energy heats the local gas to above 10^7 K. Disk blowout is probably the major cause for energy loss in this case, but the momentum acquired during the pressurized expansion phase can be large enough that the bubble still snowplows to a kpc diameter. This differs from the standard model for the origin of such shells by multiple supernovae, which may have problems with radiative cooling, evaporative losses, and disk blow-out. Evidence for giant shells with energies of \\sim10^53 ergs are summarized. Some contain no obvious central star clusters and may be GRB remnants, although sufficiently old clusters would be hard to detect. The expected frequency of GRBs in normal galaxies can account for the number of such shells.\nProgram listing for Tuesday\n",
    "text": "Previous abstract Next abstract\nSession 40 - The Interstellar Medium.\nDisplay session, Tuesday, June 09\nGamma Ray Burst (GRB) explosions can make kpc-size shells and holes in the interstellar media (ISM) of spiral galaxies if much of the energy heats the local gas to above 10^7 K. Disk blowout is probably the major cause for energy loss in this case, but the momentum acquired during the pressurized expansion phase can be large enough that the bubble still snowplows to a kpc diameter. This differs from the standard model for the origin of such shells by multiple supernovae, which may have problems with radiative cooling, evaporative losses, and disk blow-out. Evidence for giant shells with energies of \\sim10^53 ergs are summarized. Some contain no obvious central star clusters and may be GRB remnants, although sufficiently old clusters would be hard to detect. The expected frequency of GRBs in normal galaxies can account for the number of such shells.\nProgram listing for Tuesday",
    "token_count": 208,
    "url": "http://aas.org/archives/BAAS/v30n2/aas192/abs/S040015.html"
}
```

This subset can be loaded as:

```python
from datasets import load_dataset

ds = load_dataset("distilabel-internal-testing/fine-preferences-magpie-v6-tasky-7-3", "default")
```

Or simply as it follows, since there's only one configuration and is named `default`: 

```python
from datasets import load_dataset

ds = load_dataset("distilabel-internal-testing/fine-preferences-magpie-v6-tasky-7-3")
```


</details>
