Lithium Impurity Risk Prediction
Predict impurity breakthrough to battery grade from feed profile and purification conditions. Higher ROC-AUC is better.
Metric
ROC-AUC
Baseline
Lithium Impurity Risk Model
Submissions
31
Updated
2026-06-22
Leaderboard
| Rank | Submitter | Model | Type | Score | Date |
|---|---|---|---|---|---|
| 1 | p.nakamura | impurity-tab | Research implementation | 0.921 | 2026-06-22 |
| 2 | matereal | li-impurity-risk | Synthetic-data model | 0.900 | 2026-06-20 |
| 3 | s.iyer | gbm-risk | Baseline model | 0.889 | 2026-06-14 |
| 4 | d.moreau | logreg | Baseline model | 0.804 | 2026-06-01 |
Entries are reference and research submissions on the open split. Scores are illustrative and require plant-specific validation for industrial use.
Task definition
Evaluation metric
ROC-AUC
Submission rules
- 1
Report ROC-AUC and Brier score on the held-out split.
- 2
Calibration curves encouraged in submission notes.
Discussion
- s.Question
s.iyer
ML researcher · 2d
Are ensemble submissions allowed, or single-model only? Worth stating explicitly in the rules.
7 - maComment
matereal
Maintainer · 2d
Ensembles are allowed if reproducible from the submitted artifacts. We'll clarify in the next rules revision.
5
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