RAVE spectroscopy of luminous blue variables in the Large Magellanic Cloud
Bibliographic record
Abstract
Context. The RAVE spectroscopic survey for galactic structure and evolution obtains 8400–8800 Å spectra at 7500 resolving power at the UK Schmidt Telescope using the 6dF multi-fiber positioner. More than 300 000 9 ≤ IC ≤ 12 and |b| ≥ 25° southern stars have been observed to date.Aims. This paper presents the first intrinsic examination of stellar spectra from the RAVE survey, aimed at evaluating their diagnostic potential for peculiar stars and at contributing to the general understanding of luminous blue variables (LBVs).Methods. We used the multi-epoch spectra for all seven LBVs observed, between 2005 and 2008, in the Large Magellanic Cloud (LMC) by the RAVE survey.Results. We demonstrate that RAVE spectra possess significant diagnostic potential when applied to peculiar stars and, in particular, LBVs. The behaviour of the radial velocities for both emission and absorption lines, and the spectral changes between outburst and quiescence states are described and found to agree with evidence gathered at more conventional wavelengths. The wind outflow signatures and their variability are investigated, with multi-components detected in S Doradus. Photoionisation modelling of the rich emission line spectrum of R 127 shows evidence of a massive detached ionised shell that was ejected during the 1982–2000 outburst. Surface inhomogeneities in the nuclear-processed material, brought to the surface by heavy mass loss, could have been observed in S Doradus, even if alternative explanations are possible. We also detect the transition from quiescence to outburst state in R 71. Finally, our spectrum of R 84 offers one of the clearest views of its cool companion.
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 | 0.000 | 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) | 0.000 | 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 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".