Magellanic Cloud WC/WO Wolf-Rayet stars - I. Binary frequency and Roche lobe overflow formation
Bibliographic record
Abstract
A nearly complete sample of 24 Magellanic Cloud WC/WO subclass Wolf–Rayet stars is studied spectroscopically and photometrically to determine its binary frequency. Theory predicts the Roche lobe overflow produced Wolf–Rayet binary frequency to be 52±14 per cent in the Large Magellanic Cloud and 100 per cent in the Small Magellanic Cloud, not counting non-Roche lobe overflow Wolf–Rayet binaries. Lower ambient metallicity (Z) leads to lower opacity, preventing all but the most massive (hence luminous) single stars from reaching the Wolf–Rayet stage. However, theory predicts that Roche lobe overflow even in binaries of modest mass will lead to Wolf–Rayet stars in binaries with periods below approximately 200 d, for initial periods below approximately 1000 d, independent of Z. By examining their absolute continuum magnitudes, radial velocity variations, emission-line equivalent widths and full widths at half-maximum, a WC/WO binary frequency of only 13 per cent, significantly lower than the prediction, is found in the Large Magellanic Cloud. In the unlikely event that all of the cases with a less certain binary status actually turn out to be binary, current theory and observation would agree. (The Small Magellanic Cloud contains only one WC/WO star, which happens to be a binary.) The three WC+O binaries in the Large Magellanic Cloud all have periods well below 1000 d. The large majority of WC/WO stars in such environments apparently can form without the aid of a binary companion. Current evolutionary scenarios appear to have difficulty explaining either the relatively large number of Wolf–Rayet stars in the Magellanic Clouds, or the formation of Wolf–Rayet stars in general.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| 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) | 0.002 | 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".