# PubMedCausal

License: permissive (MIT); Mdexa hosting: link-only. first-hand data-scope statement(s) allow commercial use and redistribution

- Commercial use: Yes · Derivatives: Yes · Redistribution: Yes · File on Mdexa: No
- License status: Permissive (MIT)
- Mdexa hosting: Link only — License permissive: first-hand data-scope statement(s) allow commercial use and redistribution. Link only.
- Last verified: 2026-11-14
- Card: https://mdexa.com/datasets/pubmedcausal/

## Key facts

- Domain: Biomedical literature
- Content type: Annotated corpora, Literature
- Size: — — 30,000 paragraph-level samples
- Language: English
- Modality: Text
- Publisher: jaypee01
- Year: —

## Commercial use of PubMedCausal

- Commercial use: Yes.
- License status: Permissive.
- Conditions: Notice kept
Verdicts record what sources state and are not legal advice.

## PubMedCausal license evidence

first-hand data-scope statement(s) allow commercial use and redistribution

- **Hugging Face card metadata** — MIT: Statement found in snapshot s01 (readme) — "license: mit" — https://huggingface.co/datasets/jaypee01/PubMedCausal (2026-11-12; Page opened)

## Source and lineage

—

## Known issues with PubMedCausal

- Severe class imbalance: only 13.15% of samples contain annotated causality, so accuracy alone is misleading.
- Annotated relations express causal claims in the literature; they do not establish that the claims are true, and predictions are not medical advice.

## Preflight

Not run (data not ingested).

## Downloading PubMedCausal and API access

Mdexa does not serve files. Original source:
- https://huggingface.co/datasets/jaypee01/PubMedCausal

### Access recipe

- .gitattributes · 3 KB · https://huggingface.co/datasets/jaypee01/PubMedCausal/resolve/fb01de12ea3d12fe45a5a5ba173c8d113a00e949/.gitattributes
- LICENSE · 1 KB · https://huggingface.co/datasets/jaypee01/PubMedCausal/resolve/fb01de12ea3d12fe45a5a5ba173c8d113a00e949/LICENSE
- PubMedCausaldata/30k_test.json · 28.3 MB · sha256 ee4db1cea406a7387ba6696310402c5c2eb31a2cc584e42419117446c6f9e68b · https://huggingface.co/datasets/jaypee01/PubMedCausal/resolve/fb01de12ea3d12fe45a5a5ba173c8d113a00e949/PubMedCausaldata/30k_test.json
- PubMedCausaldata/30k_train.json · 28.3 MB · sha256 4cd866724d3624099f73237f1af1ec959a5a2744c607f76fc9862606459ef9b7 · https://huggingface.co/datasets/jaypee01/PubMedCausal/resolve/fb01de12ea3d12fe45a5a5ba173c8d113a00e949/PubMedCausaldata/30k_train.json
- PubMedCausaldata/validation_set.json · 2.1 MB · https://huggingface.co/datasets/jaypee01/PubMedCausal/resolve/fb01de12ea3d12fe45a5a5ba173c8d113a00e949/PubMedCausaldata/validation_set.json
- README.md · 11 KB · https://huggingface.co/datasets/jaypee01/PubMedCausal/resolve/fb01de12ea3d12fe45a5a5ba173c8d113a00e949/README.md

```sh
curl -L --create-dirs -o ".gitattributes" "https://huggingface.co/datasets/jaypee01/PubMedCausal/resolve/fb01de12ea3d12fe45a5a5ba173c8d113a00e949/.gitattributes"
curl -L --create-dirs -o "PubMedCausaldata/30k_test.json" "https://huggingface.co/datasets/jaypee01/PubMedCausal/resolve/fb01de12ea3d12fe45a5a5ba173c8d113a00e949/PubMedCausaldata/30k_test.json"
echo "ee4db1cea406a7387ba6696310402c5c2eb31a2cc584e42419117446c6f9e68b  PubMedCausaldata/30k_test.json" | sha256sum -c
curl -L --create-dirs -o "PubMedCausaldata/30k_train.json" "https://huggingface.co/datasets/jaypee01/PubMedCausal/resolve/fb01de12ea3d12fe45a5a5ba173c8d113a00e949/PubMedCausaldata/30k_train.json"
echo "4cd866724d3624099f73237f1af1ec959a5a2744c607f76fc9862606459ef9b7  PubMedCausaldata/30k_train.json" | sha256sum -c
curl -L --create-dirs -o "PubMedCausaldata/validation_set.json" "https://huggingface.co/datasets/jaypee01/PubMedCausal/resolve/fb01de12ea3d12fe45a5a5ba173c8d113a00e949/PubMedCausaldata/validation_set.json"
curl -L --create-dirs -o "README.md" "https://huggingface.co/datasets/jaypee01/PubMedCausal/resolve/fb01de12ea3d12fe45a5a5ba173c8d113a00e949/README.md"
```

## Citing PubMedCausal

No recommended citation text.

## Machine-readable

- JSON: https://mdexa.com/datasets/pubmedcausal.json
- 2026-11-14 Added via the automated pipeline and passed all checks (gates, verbatim quotes, rule engine, two independent extractions).

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