Photometric metallicity calibration with SDSS and SCUSS and its application to distant stars in the south Galactic cap
Bibliographic record
Abstract
Based on Sloan Digital Sky Survey (SDSS) g, r and South Galactic Cap of u-band Sky Survey (SCUSS) u photometry, we develop a photometric calibration for estimating the stellar metallicity from u − g and g − r colours by using the SDSS spectra of 32 542 F- and G-type main-sequence stars, which cover almost 3700 deg2 in the south Galactic cap. The rms scatter of the photometric metallicity residuals relative to spectrum-based metallicity is 0.14 dex when g − r < 0.4, and 0.16 dex when g − r > 0.4. Because of the deeper and more accurate magnitude of SCUSS u band, the estimate can be used up to the faint magnitude of g = 21. This application range of photometric metallicity calibration is wide enough so that it can be used to study metallicity distribution of distant stars. In this study, we select the Sagittarius (Sgr) stream and its neighbouring field halo stars in south Galactic cap to study their metallicity distribution. We find that the Sgr stream at the cylindrical Galactocentric coordinate of R ∼ 19 kpc, |z| ∼ 14 kpc exhibits a relative rich metallicity distribution, and the neighbouring field halo stars in our studied fields can be modelled by two-Gaussian model, with peaks, respectively, at [Fe/H] = −1.9 and −1.5.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".