The MiMeS survey of Magnetism in Massive Stars: magnetic analysis of the O-type stars
Bibliographic record
Abstract
We present the analysis performed on spectropolarimetric data of 97 O-type targets included in the framework of the Magnetism in Massive Stars (MiMeS) Survey. Mean least-squares deconvolved Stokes <it>I</it> and <it>V</it> line profiles were extracted for each observation, from which we measured the radial velocity, rotational and non-rotational broadening velocities, and longitudinal magnetic field <it>B</it><inf>&ell;</inf>. The investigation of the Stokes <it>I</it> profiles led to the discovery of two new multiline spectroscopic systems (HD 46106, HD 204827) and confirmed the presence of a suspected companion in HD 37041. We present a modified strategy of the least-squares deconvolution technique aimed at optimizing the detection of magnetic signatures while minimizing the detection of spurious signatures in Stokes <it>V</it>. Using this analysis, we confirm the detection of a magnetic field in six targets previously reported as magnetic by the MiMeS collaboration (HD 108, HD 47129A2, HD 57682, HD 148937, CPD-28 2561, and NGC 1624-2), as well as report the presence of signal in Stokes <it>V</it> in three new magnetic candidates (HD 36486, HD 162978, and HD 199579). Overall, we find a magnetic incidence rate of 7 ± 3 per cent, for 108 individual O stars (including all O-type components part of multiline systems), with a median uncertainty of the <it>B</it><inf>&ell;</inf> measurements of about 50 G. An inspection of the data reveals no obvious biases affecting the incidence rate or the preference for detecting magnetic signatures in the magnetic stars. Similar to A- and B-type stars, we find no link between the stars’ physical properties (e.g. <it>T</it><inf>eff</inf>, mass, and age) and the presence of a magnetic field. However, the Of?p stars represent a distinct class of magnetic O-type stars.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 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".