The Stellar Abundances and Galactic Evolution Survey: Photonic Passbands and Extinction Coefficients for the <i>u</i> and <i>v</i> Bands
Bibliographic record
Abstract
Abstract The Stellar Abundances and Galactic Evolution Survey (SAGES) is a multi-band photometric survey focused on estimation of stellar atmospheric parameters and interstellar extinction. In this paper we have derived photonic passbands for the intermediate-band u and v filters of the SAGES photometric system. The derived photonic passbands have been compared with those of the u and v filters of the Strömgren and SkyMapper systems. Synthetic photometry based on the derived photonic passbands could reproduce the observations very well. We have also derived observed, model-free extinction coefficients for the SAGES u and v bands (as well as the Pan-STARRS grizy bands) using the “standard pair” method. The derived reddening coefficients have been compared with those predicted by the extinction laws. Variations of reddening coefficients with effective temperatures and color excesses of B – V given by Schlegel et al. ( E ( B − V ) SFD ) have been investigated. No obvious trends or significant variations with effective temperatures have been found, but reddening coefficients for all the colors exhibit declining trends with increasing E ( B − V ) SFD , with typical relative variations of twenty-some percent from E ( B − V ) SFD ∼ 0 to 1.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.000 |
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 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".