A one-class Deep SVDD scorer trained on S2-anchored surrogates of one MMS reference event reduces 22,775 burst windows to 270 detections, 78% of which survive human screening as sheet-like or reconnection-like.
Title resolution pending
1 Pith paper cite this work, alongside 509 external citations. Polarity classification is still indexing.
1
Pith paper citing it
509
external citations · OpenAlex
fields
physics.space-ph 1years
2026 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
Shrinking the Haystack: One-Class Machine Learning Detection of Magnetosheath Current Sheets in MMS Burst Data
A one-class Deep SVDD scorer trained on S2-anchored surrogates of one MMS reference event reduces 22,775 burst windows to 270 detections, 78% of which survive human screening as sheet-like or reconnection-like.