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paperlab_reference_dataset_curation

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Curate reference datasets for PaperLab validation, including source tracing, unit normalization, uncertainty notes, license status, and citation mapping.

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How to use this skill

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Source SKILL.md: https://github.com/equinor/neqsim/blob/HEAD/neqsim-paperlab/skills/paperlab_reference_dataset_curation/SKILL.md

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PaperLab Reference Dataset Curation

When to Use

USE WHEN: extracting literature or benchmark data into files that support paper claims, book examples, or regression baselines.

Dataset Manifest Fields

{
  "dataset_id": "co2_water_solubility_2024",
  "source_citation_key": "Author2024",
  "source_type": "paper_table",
  "extraction_method": "manual_table_transcription",
  "original_units": {"temperature": "C", "pressure": "MPa"},
  "normalized_units": {"temperature": "K", "pressure": "bara"},
  "uncertainty": "reported standard deviation where available",
  "license_or_use_note": "cite only; do not redistribute full source text",
  "files": ["reference_data/co2_water_solubility_2024.csv"]
}

Workflow

  1. Identify source and citation key.
  2. Extract only the data needed for validation.
  3. Preserve original units and normalize into a separate column or metadata field.
  4. Add uncertainty and data-quality notes.
  5. Link each dataset to hypotheses, figures, and claims.

Pass Criteria

  • Every numeric column has a unit.
  • Every dataset has a citation and extraction method.
  • Public outputs avoid restricted source text.

Safety Rules

  • Do not redistribute copyrighted tables wholesale when a minimal derived dataset is enough.
  • Never silently round or smooth data used for validation.
  • Mark transcription uncertainty when data was read from figures.