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pretty_name: NeuroClaimBench
language:
- en
license: cc-by-4.0
size_categories:
- n<1K
tags:
- neuroimaging
- scientific-reporting
- benchmark
- claim-validation
configs:
- config_name: cases
default: true
data_files:
- split: test
path: cases.jsonl
- config_name: references
data_files:
- split: test
path: references.jsonl
- config_name: tasks
data_files:
- split: test
path: tasks.jsonl
- config_name: outcomes
data_files:
- split: test
path: outcomes.jsonl
---
# NeuroClaimBench v2.1
NeuroClaimBench evaluates whether a system supports or withholds a
neuroimaging claim.
The package contains 489 executable tasks: 279 scientific claims, 150
constructed stress controls, and 60 external-transfer claims and controls.
The inventory also includes 55 cases excluded from execution because of
ambiguous question-plan alignment, unavailable analysis inputs, or invalid designs.
Questions, analysis plans, reference labels, and recorded CONFIRM outcomes
are provided as JSONL files.
**Code:** [CONFIRM](https://github.com/yuxiangwei0808/CONFIRM) · **Dataset:** [Hugging Face](https://huggingface.co/datasets/stanjsx/NeuroClaimBench)
## Load from Hugging Face
Install the dataset library:
```bash
python -m pip install datasets
```
Load an individual record collection:
```python
from datasets import load_dataset
tasks = load_dataset("stanjsx/NeuroClaimBench", "tasks", split="test", revision="v2.1.1")
print(tasks[0]["task_id"])
print(tasks[0]["contract"])
```
The configurations are `cases` (544 rows), `references` (544), `tasks` (489),
and `outcomes` (489). Each uses a single `test` split. The default configuration
is `cases`; these are record collections for evaluation, with links described
in the [data dictionary](DATA_DICTIONARY.md).
To download the complete benchmark for the command-line tools:
```python
from huggingface_hub import snapshot_download
snapshot_download(
repo_id="stanjsx/NeuroClaimBench",
repo_type="dataset",
revision="v2.1.1",
local_dir="neuroclaimbench-v2.1",
)
```
## Install the tools
Use Python 3.10 or newer. CONFIRM supplies the `neuroclaimbench` command.
Download `confirm-0.1.1-py3-none-any.whl` from the
[CONFIRM v0.1.1 release](https://github.com/yuxiangwei0808/CONFIRM/releases/tag/v0.1.1)
into the directory containing the extracted `neuroclaimbench-v2.1` folder.
Run from that parent directory:
```bash
python -m venv .venv
source .venv/bin/activate
python -m pip install ./confirm-0.1.1-py3-none-any.whl
```
To install from source,
extract `confirm-0.1.1.zip` and run `python -m pip install ./confirm-0.1.1`
from its parent directory. An existing CONFIRM installation provides the
same benchmark commands.
## Verify and score
Run from the directory containing the extracted benchmark folder:
```bash
neuroclaimbench verify --benchmark neuroclaimbench-v2.1
neuroclaimbench predictions --benchmark neuroclaimbench-v2.1 \
--standard full --out outputs/confirm-full.jsonl
neuroclaimbench score --benchmark neuroclaimbench-v2.1 \
--predictions outputs/confirm-full.jsonl
```
These commands verify all files, export 489 decisions from the recorded
gate results, and score agreement with the reference labels. They require
no cohort data or model calls. Choose a new output filename for each export.
## Guides
- [Python loading, metrics, and evaluation](USAGE.md)
- [File and field definitions](DATA_DICTIONARY.md)
- [Cohort data and exact-input requirements](DATA_ACCESS.md)
Executing a task requires its corresponding prepared cohort files. The
metadata package contains no participant tables, random-control assignment
tables, or PubMed abstracts.
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