The MMS Dayside Magnetic Reconnection Locations During Phase 1 and Their Relation to the Predictions of the Maximum Magnetic Shear Model
Bibliographic record
Abstract
Abstract Several studies have validated the accuracy of the maximum magnetic shear model to predict the location of the reconnection site at the dayside magnetopause. These studies found agreement between model and observations for 74% to 88% of events examined. It should be noted that, of the anomalous events that failed the prediction of the model, 72% shared a very specific parameter range. These events occurred around equinox for an interplanetary magnetic field (IMF) clock angle of about 240°. This study investigates if this remarkable grouping of events is also present in data from the recently launched MMS. The MMS magnetopause encounter database from the first dayside phase of the mission includes about 4,500 full and partial magnetopause crossings and flux transfer events. We use the known reconnection line signature of switching accelerated ion beams in the magnetopause boundary layer to identify encounters with the reconnection region and identify 302 events during phase 1a when the spacecraft are at reconnection sites. These confirmed reconnection locations are compared with the predicted location from the maximum magnetic shear model and revealed an 80% agreement. The study also revealed the existence of anomalous cases as mentioned in an earlier study. The anomalies are concentrated for times around the equinoxes together with IMF clock angles around 140° and 240°. Another group of anomalies for the same clock angle ranges was found during December events.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".