Separating DP1 and DP2 current pattern contributions to substorm-like intensifications in SML
Bibliographic record
Abstract
Substorms have been identified from negative bays in the AL/SML index, which traces the minimum northward ground magnetic deflection at auroral latitudes, produced by enhancements of the westward electrojet. For substorms, negative bays are caused by the closure of the Substorm Current Wedge through the ionosphere, typically localised to the nightside and centred around 23-00 magnetic local time (MLT). In this case, the equivalent current pattern that causes the magnetic deflections is given the name Disturbance Polar (DP) 1. However, negative bays may also form when the westward electrojet is enhanced by increased convection, driving Pedersen and Hall currents in the auroral zone. Convection enhancements also strengthen the eastward electrojet, monitored by the maximum northward ground magnetic deflection as the AU/SMU index. In this case, the equivalent current pattern that produces the magnetic deflections is called DP2. Unlike other substorm identification methods, the SOPHIE technique by Forsyth et al. (2015) attempts to distinguish between the DP1 and DP2 enhancements that cause substorm-like SML bays by also examining the SMU index. Despite this, we find evidence that between January 1997 and December 2019 up to 59% of the 30329 events originally identified as substorms come from enhancements of DP2 on top of the 2627 convection enhancement events already identified. We explore ways to improve substorm identification using auroral indices to fully separate the DP1 and DP2 bays, but conclude that there is insufficient information in the auroral indices alone to achieve this.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".