The Araucaria Project. VLT spectra of blue supergiants in WLM: classification and first abundances
Bibliographic record
Abstract
As part of the Araucaria Project, we present the first spectral catalog of supergiant stars in the Local Group dwarf irregular galaxy WLM. In assigning a spectral classification to these stars we accounted for the low metal content of WLM relative to the galactic standards used in the MK process, by using classification criteria developed for B and A supergiants contained in the Small Magellanic Cloud. Our spectral catalog shows that our higher S/N spectroscopic sample of 19 objects contains at least 6 early-B (B0-B5) supergiants and 6 late-B and early-A (B8-A2) stars of luminosity class between Ia and II, as well as an O7~V star and an O9.7 Ia star. The spectra of several of these stars is of sufficiently high quality for a determination of the stellar parameters and abundances. We have acquired also a second set of lower S/N spectra for mostly BA stars, however their quality does not allow a further analysis. We have carried out a quantitative analysis for three early-B supergiants. The mean oxygen abundance we derive is 12+log(O/H)=7.83 +/- 0.12. This value agrees very well with the measurement that is obtained from HII regions. We therefore find no additional evidence for the discrepancy between stellar and nebular oxygen abundances measured for a single A-type supergiant by Venn et al. The analysis of B- and A-type supergiants yields compatible results for nitrogen, silicon and magnesium. We show that the photometric variability of the blue supergiants included in our spectroscopic sample is negligible for the use of these stars as distance indicators.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.007 |
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".