Quantitative Studies of the Far‐Ultraviolet, Ultraviolet, and Optical Spectra of Late O‐ and Early B‐Type Supergiants in the Magellanic Clouds
Bibliographic record
Abstract
We present quantitative studies of eight late O- and early B-type supergiants in the Magellanic Clouds using far-ultraviolet Far Ultraviolet Spectroscopic Explorer , ultraviolet International Ultraviolet Explorer / Hubble Space Telescope , and optical VLT-UVES spectroscopy. Temperatures, mass-loss rates, and CNO abundances are obtained using the non-LTE, spherical, line-blanketed model atmosphere code of Hillier & Miller. We support recent results for lower temperatures of OB-type supergiants as a result of stellar winds and blanketing, which amounts to ~2000 K at B0 Ia. In general, Hα-derived mass-loss rates are consistent with UV and far-UV spectroscopy, although from consideration of the S IV λλ1063, 1073 doublet, clumped winds are preferred over homogenous models. AV 235 (B0 Iaw) is a notable exception, which has an unusually strong Hα profile that is inconsistent with the other Balmer lines and UV wind diagnostics. We also derive CNO abundances for our sample, revealing substantial nitrogen enrichment, with carbon and oxygen depletion. Our results are supported by comparison with the Galactic supergiant HD 2905 (BC0.7 Ia) for which near-solar CNO abundances are obtained. This bolsters previous suggestions that "normal" OB-type supergiants exhibit atmospheric compositions indicative of partial CNO processing.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".