starkAhmed43/leak-curber-kcat-km
Leak CURBER: joint kcat–Km prediction For each SMILES–sequence pair, predict log10_kcat and log10_km. Both targets are base-10 logarithms. Do not predict raw values. Files train.parquet: id, smiles, sequence, log10_kcat, and log10_km. 42,524 rows. val_inputs.parquet: id, smiles, and sequence. 1,901 rows. Output and metric Submit a CSV with the columns id,log10_kcat,log10_km. For each target, we compute the Spearman rank correlation (SCC) and the… See the full description on the dataset page: https://huggingface.co/datasets/starkAhmed43/leak-curber-kcat-km.
| Author / organization | starkAhmed43 |
|---|---|
| Downloads | 142 (as reported by Hugging Face) |
| Likes | 3 |
| Created | 21 October 2026 |
| Last updated at source | 23 October 2026 |
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142 now (+142 since 2026-10-21). Counts as reported by the source, snapshotted daily by Silytics.
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- 27 Oct 2026 Description: Leak CURBER: joint kcat–Km prediction Predict both log10_kcat and log10_km for each SMILES–sequence input. Both targets use base-10 logarithms of the source values. Do not predict raw values. Training data include both labels. Validation in → Leak CURBER: joint kcat–Km prediction For each SMILES–sequence pair, predict log10_kcat and log10_km. Both targets are base-10 logarithms. Do not predict raw values. Files train.parquet: id, smiles, sequence, log10_kcat, and log10_km. 42,52
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