Rotational and pulsational variability in the TESS light curve of HD 27463
Bibliographic record
Abstract
ABSTRACT The new photometric data on pulsating Ap star HD 27463 obtained recently with the Transiting Exoplanet Survey Satellite (TESS) are analysed to search for variability. Our analysis shows that HD 27463 exhibits two types of photometric variability. The low-frequency variability with the period P = 2.834 274 ± 0.000 008 d can be explained in terms of axial stellar rotation assuming the oblique magnetic rotator model and presence of surface abundance/brightness spots, while the detected high-frequency variations are characteristics of δ Scuti pulsations. From the analysis of Balmer line profiles visible in two FEROS spectra of HD 27463 we have derived its effective temperature and surface gravity, finding values that are close to those published for this star in the TESS Input Catalogue (TIC). Knowing the rotation period and the v sin i value estimated from the fitting of Balmer line profiles we found that the rotational axis is inclined to the line of sight with an angle of $i=33\pm 8\deg$. Our best-fitting model of the observed pulsation modes results in an overshoot parameter value fov = 0.014 and values of global stellar parameters that are in good agreement with the data reported in the TIC and with the data derived from fitting Balmer line profiles. This model indicates an age of 5.0 ± 0.4 × 108 yr, which corresponds to a core hydrogen fraction of 0.33.
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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 | 0.001 |
| 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) | 0.002 | 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".