RR Lyrae studies with <i>Kepler</i>: showcasing RR Lyr
Bibliographic record
Abstract
Abstract Four years into the Kepler mission, an updated review on the results for RR Lyrae stars is in order. More than 50 RR Lyrae stars in the Kepler field are observed with Kepler and each one of them can provide us with new insight into this class of pulsating stars. Ground-based spectroscopy of the Kepler targets allows us to narrow down their physical parameters. Previously, we already reported a 50% occurrence rate of modulation in the RRab stars, a large variety of modulation behavior, period doubling in several Blazhko stars, the detection of higher- overtone radial modes, probable non-radial modes and new types of multiple-mode RR Lyrae pulsators, among both the RRab and the RRc stars. In addition, the quasi-continuous photometry obtained over several years with Kepler allows one to observe changes in Blazhko behavior and additional longer cycles. These observations have sparked new theoretical modelling efforts. In this short paper we showcase RR Lyr itself. The star has been observed with Kepler in short cadence, and some remarkable features of its pulsation behavior are unveiled in this long-studied prototype, through the Kepler photometry and additional spectroscopic data.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".