MOBSTER – II. Identification of rotationally variable A stars observed with TESS in sectors 1–4
Bibliographic record
Abstract
Recently, high-precision optical 2-min cadence light curves obtained with TESS for targets located in the mission’s defined first four sectors have been released. The majority of these high-cadence and high-precision measurements currently span |${\sim }28\, {\rm d}$|, thereby allowing periodic variability occurring on time-scales |${\lesssim }14\, {\rm d}$| to potentially be detected. Magnetic chemically peculiar (mCP) A-type stars are well known to exhibit rotationally modulated photometric variability that is produced by inhomogeneous chemical abundance distributions in their atmospheres. While mCP stars typically exhibit rotation periods that are significantly longer than those of non-mCP stars, both populations exhibit typical periods |${\lesssim }10\, {\rm d}$|; therefore, the early TESS releases are suitable for searching for rotational modulation of the light curves of both mCP and non-mCP stars. We present the results of our search for A-type stars that exhibit variability in their TESS light curves that is consistent with rotational modulation based on the first two data releases obtained from sectors 1 to 4. Our search yielded 134 high-probability candidate rotational variables – 60 of which have not been previously reported. Approximately half of these stars are identified in the literature as Ap (mCP) stars. Comparisons between the subsample of high-probability candidate rotationally variable Ap stars and the subsample of stars that are not identified as Ap reveal that the latter subsample exhibits statistically (i) shorter rotation periods and (ii) significantly lower photometric amplitudes.
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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 | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".