An Ensemble of Trees, Self-Normalizing Networks and a Foundation Model for Tox21 Toxicity Prediction

A seven-model ensemble (random forest, ExtraTrees, two LightGBM models, two self-normalizing neural networks and the CheMeleon foundation model) for the 12-task Tox21 toxicity benchmark, submitted to the JKU Linz Tox21 Reproducible Leaderboard. Trained only on the ml-jku/tox21 data. Cross-validation mean ROC-AUC 0.854 and official validation-set mean ROC-AUC 0.785. Code and training script: https://huggingface.co/spaces/ruebenkadosh/tox21-ensemble

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-11-06
DOI
https://doi.org/10.5281/zenodo.24003188
Primary Topic
Computational Drug Discovery Methods
Type
preprint
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preprint

An Ensemble of Trees, Self-Normalizing Networks and a Foundation Model for Tox21 Toxicity Prediction

Rueben Kadosh
1 links
Zenodo (CERN European Organization for Nuclear Research)
Computational Drug Discovery Methods
preprint

An Ensemble of Trees, Self-Normalizing Networks and a Foundation Model for Tox21 Toxicity Prediction

Rueben Kadosh
preprint en

Abstract

A seven-model ensemble (random forest, ExtraTrees, two LightGBM models, two self-normalizing neural networks and the CheMeleon foundation model) for the 12-task Tox21 toxicity benchmark, submitted to the JKU Linz Tox21 Reproducible Leaderboard. Trained only on the ml-jku/tox21 data. Cross-validation mean ROC-AUC 0.854 and official validation-set mean ROC-AUC 0.785. Code and training script: https://huggingface.co/spaces/ruebenkadosh/tox21-ensemble

Zenodo (CERN European Organization for Nuclear Research)
Computational Drug Discovery Methods
DOIOpen Access PDFOpenAlex
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An Ensemble of Trees, Self-Normalizing Networks and a Foundation Model for Tox21 Toxicity Prediction — Rueben Kadosh · Zenodo (CERN European Organization for Nuclear Research) (2026) | TGRS Research Map | TGRS