README.md

metadata

language:
  - en
license: other
task_categories:
  - text-classification
  - text-generation
pretty_name: Cochrane Screening SFT
tags:
  - systematic-review
  - cochrane
  - title-abstract-screening
  - medical
  - peft
  - sft
size_categories:
  - 100K<n<1M
configs:
  - config_name: default
    data_files:
      - split: train
        path: train.jsonl
      - split: validation
        path: val.jsonl
      - split: test
        path: test.jsonl
  - config_name: heldout_reviews1
    data_files:
      - split: test
        path: heldout_reviews1.jsonl
  - config_name: heldout_reviews2
    data_files:
      - split: test
        path: heldout_reviews2.jsonl
  - config_name: heldout_reviews3
    data_files:
      - split: test
        path: heldout_reviews3.jsonl
dataset_info:
  - config_name: default
    features:
      - name: messages
        list:
          - name: role
            dtype: string
          - name: content
            dtype: string
      - name: row_id
        dtype: int64
      - name: label
        dtype: string
    splits:
      - name: train
        num_examples: 416799
      - name: validation
        num_examples: 46311
      - name: test
        num_examples: 26673
  - config_name: heldout_reviews1
    features:
      - name: messages
        list:
          - name: role
            dtype: string
          - name: content
            dtype: string
      - name: row_id
        dtype: int64
      - name: label
        dtype: string
    splits:
      - name: test
        num_examples: 26858
  - config_name: heldout_reviews2
    features:
      - name: messages
        list:
          - name: role
            dtype: string
          - name: content
            dtype: string
      - name: row_id
        dtype: int64
      - name: label
        dtype: string
    splits:
      - name: test
        num_examples: 4391
  - config_name: heldout_reviews3
    features:
      - name: messages
        list:
          - name: role
            dtype: string
          - name: content
            dtype: string
      - name: row_id
        dtype: int64
      - name: label
        dtype: string
    splits:
      - name: test
        num_examples: 19007

Cochrane Screening SFT

Supervised fine-tuning (SFT) chat dataset for Cochrane-style title and abstract screening.

Each example is a chat conversation that asks a model to predict a screening decision (include / exclude / uncertain) and a short justification (reason).

Code: ljwa2323/cochrane-screening-slm

Dataset summary

Split / config	Records	Role
train	416,799	LoRA SFT training
validation	46,311	Training-time validation (10% stratified holdout from development data)
test	26,673	Internal held-out test split
heldout_reviews1	26,858	External reviews (random Cochrane set)
heldout_reviews2	4,391	External reviews (HIV-focused set)
heldout_reviews3	19,007	External reviews (heart/CVD-focused set)

Label mapping used when building the dataset:

• 0.0 -> exclude
• 0.5 -> uncertain
• 1.0 -> include

Approximate label counts on the development-derived set (train+val source):

• exclude: 221,129
• uncertain: 160,861
• include: 81,120

Data fields

Each *.jsonl line contains:

Field	Type	Description
messages	list	Chat turns: system, user, assistant
row_id	int	Source row id
label	string	Gold label: include / exclude / uncertain

The assistant target is a JSON object:

{"label": "include|exclude|uncertain", "reason": "<brief explanation>"}

How to load

from datasets import load_dataset

# Internal splits
ds = load_dataset("deepcoder2024/cochrane-screening-sft")
print(ds)

# External held-out reviews
hr1 = load_dataset("deepcoder2024/cochrane-screening-sft", "heldout_reviews1")
hr2 = load_dataset("deepcoder2024/cochrane-screening-sft", "heldout_reviews2")
hr3 = load_dataset("deepcoder2024/cochrane-screening-sft", "heldout_reviews3")

Tip: ignore *_manifest.json files when loading. They are metadata only and should not be parsed as chat examples.

Intended use

• Fine-tune small language models (e.g., Qwen3 LoRA) for title/abstract screening
• Evaluate screening label + reason generation on internal and external review sets

Out-of-scope use

• Not a substitute for expert systematic-review judgment
• Not intended for clinical decision-making about individual patients
• Labels and reasons are for research / screening-assistance experiments only

Related models

• deepcoder2024/Qwen3-1.7B-LoRA-Cochrane-Screening
• deepcoder2024/Qwen3-4B-LoRA-Cochrane-Screening
• deepcoder2024/Qwen3-8B-LoRA-Cochrane-Screening

Citation

If you use this dataset, please cite the associated project repository:

@misc{cochrane_screening_sft,
  title        = {Cochrane Screening SFT Dataset},
  author       = {deepcoder2024},
  year         = {2026},
  howpublished = {\\url{https://huggingface.co/datasets/deepcoder2024/cochrane-screening-sft}}
}