Spectroscopic metallicity determinations for W UMa-type binary stars1
Bibliographic record
Abstract
This study is an attempt to determine the metallicities of WUMa-type binary stars using spectroscopy. ~4,500 spectra collected at the David Dunlap Observatory were subject to the same Broadening Function processing to determine the combined line strength in the spectral window centered on the MgI triplet (5080-5285A). Individual integrated BF's were phase averaged to derive a single line-strength indicator. The sample was limited to 90 EW binaries with the strict phase-constancy of colors and without spectral contamination by companions. The best defined results were obtained for a F-type sub-sample (0.32<(B-V)0<0.62) of 52 stars for which the BF strengths could be interpolated in the model predictions. The metallicities, [M/H], for the F-type sub-sample indicate abundances roughly similar to the solar [M/H], but with a large scatter which is partly due to combined random and systematic errors. Because of a color trend resulting from limitations in our approach, we set the scale of metallicities to correspond to that derived from the m_1 index of the Stromgren photometry for F-type binaries. The trend-adjusted [M/H]1 are distributed within -0.65<[M/H]1<+0.50, with the spread reflecting genuine metallicity differences between stars. One half of the F-sub-sample binaries have [M/H]1 within -0.37<[M/H]1 +0.10, a median of -0.04 and a mean of -0.10, with a tail towards low metallicities, and a possible bias against very high metallicities. A parallel study of kinematic data, utilizing the most reliable and recently obtained proper motion and radial velocity data for 78 stars of the full sample, shows that the F-type sub-sample binaries have similar kinematic properties to solar neighborhood, thin-disk dwarfs with ages about 3 - 5.5 Gyr. The F-type binaries which appear to be older than the rest tend to have systematically smaller mass-ratios than most of the EW binaries of the same period.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".