MODEL_CARD.md

# Model card - tox21_chemprop_classifier
### Model details
- Model name: Chemprop Message Passing Neural Network Tox21 Baseline
- Developer: MIT (trained by JKU Linz)
- Paper URL: https://pubs.acs.org/doi/full/10.1021/acs.jcim.3c01250
- Model type / architecture:
    - Message Passing Neural Network implemented using Chemprop.
    - Hyperparameters: [link to config](https://huggingface.co/spaces/ml-jku/tox21_chemprop_classifier/blob/main/config/config.toml)
    – A multitask network is trained for all Tox21 targets.
- Inference: Access via FastAPI endpoint. Upon receiving a Tox21 prediction request,
the model generates and returns predictions for all Tox21 targets simultaneously.
- Model version: v0
- Model date: 14.10.2025
- Reproducibility: Code for full training is available and enables retraining of the model from
scratch.

### Intended use
This model serves as a baseline benchmark for evaluating and comparing toxicity prediction
methods across the 12 pathway assays of the Tox21 dataset. It is not intended for clinical
decision-making without experimental validation.

### Metric
Each Tox21 task is evaluated using the area under the receiver operating characteristic curve
(AUC). Overall performance is reported as the mean AUC across all individual tasks.

### Training data
Tox21 training and validation sets.

### Evaluation data
Tox21 test set.