METAL ABUNDANCES, RADIAL VELOCITIES, AND OTHER PHYSICAL CHARACTERISTICS FOR THE RR LYRAE STARS IN THE<i>KEPLER</i>FIELD
Bibliographic record
Abstract
Spectroscopic iron-to-hydrogen ratios, radial velocities, atmospheric parameters, and new photometric analyses are presented for 41 RR Lyrae stars (and one probable high-amplitude δ Sct star) located in the field-of-view of the Kepler space telescope. Thirty-seven of the RR Lyrae stars are fundamental-mode pulsators (i.e., RRab stars) of which sixteen exhibit the Blazhko effect. Four of the stars are multiperiodic RRc pulsators oscillating primarily in the first-overtone mode. Spectroscopic [Fe/H] values for the 34 stars for which we were able to derive estimates range from −2.54 ± 0.13 (NR Lyr) to −0.05 ± 0.13 dex (V784 Cyg), and for the 19 Kepler -field non-Blazhko stars studied by Nemec et al. the abundances agree will with their photometric [Fe/H] values. Four non-Blazhko RR Lyrae stars that they identified as metal-rich (KIC 6100702, V2470 Cyg, V782 Cyg and V784 Cyg) are confirmed as such, and four additional stars (V839 Cyg, KIC 5520878, KIC 8832417, KIC 3868420) are also shown here to be metal-rich. Five of the non-Blazhko RRab stars are found to be more metal-rich than [Fe/H] ∼−0.9 dex while all of the 16 Blazhko stars are more metal-poor than this value. New P – –[Fe/H] relationships are derived based on ∼970 days of quasi-continuous high-precision Q0–Q11 long- and short-cadence Kepler photometry. With the exception of some Blazhko stars, the spectroscopic and photometric [Fe/H] values are in good agreement. Several stars with unique photometric characteristics are identified, including a Blazhko variable with the smallest known amplitude and frequency modulations (V838 Cyg).
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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 | 0.002 | 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 | 0.001 |
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".