The incidence of magnetic fields in massive stars: An overview of the MiMeS survey component
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
With only a handful of known magnetic massive stars, there is a troubling deficit in the scope of our knowledge of the influence of magnetic fields on stellar evolution, and almost no empirical basis for understanding how fields modify mass loss and rotation in massive stars. Most remarkably, there is still no solid consensus regarding the origin physics of these fields - whether they are fossil remnants, or produced by contemporaneous dynamos, or some combination of these mechanisms. This article will present an overview of the Survey Component of the MiMeS Large Programs, the primary goal of which is to search for Zeeman signatures in the circular polarimetry of massive stars (stars with spectral types B3 and hotter) that were previously unknown to host any magnetic field. To date, the MiMeS collaboration has collected more than 550 high-resolution spectropolarimetric observations with ESPaDOnS and NARVAL of nearly 170 different stars, from which we have discovered 14 new magnetic stars.
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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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it