The First APOKASC Catalog of Kepler Dwarf and Subgiant Stars
Bibliographic record
Abstract
Abstract We present the first APOKASC catalog of spectroscopic and asteroseismic data for dwarfs and subgiants. Asteroseismic data for our sample of 415 objects have been obtained by the Kepler mission in short (58.5 s) cadence, and light curves span from 30 up to more than 1000 days. The spectroscopic parameters are based on spectra taken as part of the Apache Point Observatory Galactic Evolution Experiment and correspond to Data Release 13 of the Sloan Digital Sky Survey. We analyze our data using two independent scales, the spectroscopic values from DR13 and those derived from SDSS griz photometry. We use the differences in our results arising from these choices as a test of systematic temperature uncertainties and find that they can lead to significant differences in the derived stellar properties. Determinations of surface gravity ( ), mean density ( ), radius ( R ), mass ( M ), and age ( τ ) for the whole sample have been carried out by means of (stellar) grid-based modeling. We have thoroughly assessed random and systematic error sources in the spectroscopic and asteroseismic data, as well as in the grid-based modeling determination of the stellar quantities provided in the catalog. We provide stellar properties determined for each of the two scales. The median combined (random and systematic) uncertainties are 2% (0.01 dex; ), 3.4% ( ), 2.6% ( R ), 5.1% ( M ), and 19% ( τ ) for the photometric scale and 2% ( ), 3.5% ( ), 2.7% ( R ), 6.3% ( M ), and 23% ( τ ) for the spectroscopic scale. We present comparisons with stellar quantities in the asteroseismic catalog by Chaplin et al. that highlight the importance of having metallicity measurements for determining stellar parameters accurately. Finally, we compare our results with those coming from a variety of sources, including stellar radii determined from TGAS parallaxes and asteroseismic analyses based on individual frequencies. We find a very good agreement for all inferred quantities. The latter comparison, in particular, gives strong support to the determination of stellar quantities based on global seismology, a relevant result for future missions such as TESS and PLATO .
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.003 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".