A NON-LTE ANALYSIS OF THE HOT SUBDWARF O STAR BD+28°4211. I. THE UV SPECTRUM
Bibliographic record
Abstract
We present a detailed analysis of the UV spectrum of the calibration star BD+28°4211 using high-quality spectra obtained with the Hubble Space Telescope and Far-Ultraviolet Spectroscopic Explorer satellites. To this aim, we compare quantitatively the observed data with model spectra obtained from state-of-the-art non-LTE metal line-blanketed model atmospheres and synthetic spectra calculated with TLUSTY and SYNSPEC. We thus determine in a self-consistent way the abundances of 11 elements with well-defined lines in the UV, namely those of C, N, O, F, Mg, Si, P, S, Ar, Fe, and Ni. The derived abundances range from about solar to 1/10 solar. We find that the overall quality of the derived spectral fits is very satisfying. Our spectral analysis can be used to constrain rather tightly the effective temperature of BD+28°4211 to a value of T eff = 82, 000 ± 5000 K. We also estimate conservatively that its surface gravity falls in the range log g = 6.2 . Assuming that the Hipparcos measurement for BD+28°4211 is fully reliable and that our model atmospheres are reasonably realistic, we can reconcile our spectroscopic constraints with the available parallax measurement only if the mass of BD+28°4211 is significantly less than the canonical value of 0.5 M ☉ for a representative post-extended horizontal branch star.
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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 | 0.000 |
| 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".