Tokamak-SI: Interpreting Tokamak Discharges with Labeled Catalogs

Tokamak-SI is a unified, time‑aligned, categorical dataset that aggregates labels and labeling methods from numerous prior studies to identify phenomena in DIII‑D tokamak discharges, including confinement, detachment, AE, ELM, sawtooth, TM, and resistive wall modes. Models trained on Tokamak-SI can extend labeling to new shots and match or outperform earlier detectors for AE, ELM, and TM detection. The dataset is designed to support task‑specific benchmarking, physics‑searchable archives, and direct event identification during experiments.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv AI.

• benchmarks