Photometric variability of the Herbig Ae star HD 37806
Bibliographic record
Abstract
Context. The more massive counterparts of T Tauri stars, the Herbig Ae/Be stars, are known to vary in a complex way with no variability mechanism clearly identified. Aims. We attempt to characterize the optical variability of HD 37806 (MWC 120) on time scales ranging between minutes and several years. Methods. A continuous, one-minute resolution, 21 day-long sequence of MOST (Microvariability & Oscillations of STars) satellite observations has been analyzed using wavelet, scalegram and dispersion analysis tools. The MOST data have been augmented by sparse observations over 9 seasons from ASAS (All Sky Automated Survey), by previously non-analyzed ESO (European Southern Observatory) data partly covering 3 seasons and by archival measurements dating back half a century ago. Results. Mutually superimposed flares or accretion instabilities grow in size from about 0.0003 of the mean flux on a time scale of minutes to a peak-to-peak range of < 0.05 on a time scale of a few years. The resulting variability has properties of stochastic “red” noise, whose self-similar characteristics are very similar to those observed in cataclysmic binary stars, but with much longer characteristic time scales of hours to days (rather than minutes) and with amplitudes which appear to cease growing in size on time scales of tens of years. In addition to chaotic brightness variations combined with stochastic noise, the MOST data show a weakly defined cyclic signal with a period of about 1.5 days, which may correspond to the rotation of the 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 | 0.000 | 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".