IMPROVED DETERMINATION OF THE ATMOSPHERIC PARAMETERS OF THE PULSATING sdB STAR FEIGE 48
Bibliographic record
Abstract
As part of a multifaceted effort to better exploit the asteroseismological potential of the pulsating sdB star Feige 48, we present an improved spectroscopic analysis of that star based on new grids of NLTE, fully line-blanketed model atmospheres. To that end, we gathered four high signal-to-noise ratio time-averaged optical spectra of varying spectral resolutions from 1.0 Å to 8.7 Å, and we made use of the results of four independent studies to fix the abundances of the most important metals in the atmosphere of Feige 48. The mean atmospheric parameters we obtained from our four spectra of Feige 48 are: T eff = 29,850 ± 60 K, log g = 5.46 ± 0.01, and log N (He)/ N (H) = −2.88 ± 0.02. We also modeled, for the first time, the He ii line at 1640 Å from the STIS archive spectrum of the star, and with this line we found an effective temperature and a surface gravity that match well with the values obtained with the optical data. With some fine tuning of the abundances of the metals visible in the optical domain, we were able to achieve a very good agreement between our best available spectrum and our best-fitting synthetic one. Our derived atmospheric parameters for Feige 48 are in rather good agreement with previous estimates based on less sophisticated models. This underlines the relatively small effects of the NLTE approach combined with line blanketing in the atmosphere of this particular star, implying that the current estimates of the atmospheric parameters of Feige 48 are reliable and secure.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.001 | 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".