Properties and nature of Be stars
Bibliographic record
Abstract
Context. One way to understand the still mysterious Be phenomenon is to study the time variations of particular Be stars with a long observational history. ζ Tau is one obvious candidate.Aims. Using our rich series of spectral and photometric observations and a critical compilation of available radial velocities, spectrophotometry of Hα, and photometry, we characterize the pattern of time variations of ζ Tau over about a century. Our goal is to find the true timescales of its variability and confront them with the existing models related to various aspects of the Be phenomenon.Methods. Spectral reductions were carried out using the IRAF and SPEFO programs. The HEC22 program was used for both photometric reductions and transformations to . Orbital solutions were derived with the latest publicly available version of the program FOTEL, period analyses employed both the PDM and Fourier techniques – programs HEC27 and PERIOD04.Results. We derived a new orbital ephemeris HJD (2447025.6±1.8) + (132987 ±0050) . The analysis of long-term spectral and light variations shows a clear correlation between the RV and changes, and a very complex behaviour of the light changes. The character of the orbital light and changes varies from season to season.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".