A photometric study of the nova-like variable TT Arietis with the MOST satellite
Bibliographic record
Abstract
Variability on all time scales between seconds and decades is typical for cataclysmic variables (CVs). One of the brightest and best studied CVs is TT Ari, a nova-like variable which belongs to the VY Scl subclass, characterized by occasional low states in their light curves. It is also known as a permanent superhumper at high state, revealing "positive" (P_S > P_0) as well as "negative" (P_S < P_0) superhumps, where P_S is the period of the superhump and P_0 the orbital period. TT Ari was observed by the Canadian space telescope MOST for about 230 hours nearly continuously in 2007, with a time resolution of 48 seconds. Here we analyze these data, obtaining a dominant "negative" superhump signal with a period P_S = 0.1331 days and a mean amplitude of 0.09 mag. Strong flickering with amplitudes up to 0.2 mag and peak-to-peak time scales of 15-20 minutes is superimposed on the periodic variations. We found no indications for significant quasi-periodic oscillations with periods around 15 minutes, reported by other authors. We discuss the known superhump behaviour of TT Ari during the last five decades and conclude that our period value is at the upper limit of all hitherto determined "negative" superhump periods of TT Ari, before and after the MOST run.
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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 | 0.002 | 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) | 0.001 | 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".