First empirical constraints on the low Hα mass-loss rates of magnetic O-stars
Bibliographic record
Abstract
Abstract A small subset of Galactic O-stars possess surface magnetic fields that alter the outflowing stellar wind by magnetically confining it. Key to the magnetic confinement is that it induces rotational modulation of spectral lines over the full EM domain; this allows us to infer basic quantities, e.g., mass-loss rate and magnetic geometry. Here, we present an empirical study of the Hα line in Galactic magnetic O-stars to constrain the mass fed from the stellar base into the magnetosphere, using realistic multi-dimensional magnetized wind models, and compare with theoretical predictions. Our results suggest that it may be reasonable to use mass-feeding rates from non-magnetic wind theory if the absolute mass-loss rate is scaled down according to the amount of wind material falling back upon the stellar surface. This provides then some empirical support to the proposal that such magnetic O-stars might evolve into heavy stellar-mass black holes (Petit et al.2017).
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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 | 0.005 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".