FIDUCIAL STELLAR POPULATION SEQUENCES FOR THE <i>u</i>′<i>g</i>′<i>r</i>′<i>i</i>′<i>z</i>′ SYSTEM
Bibliographic record
Abstract
We describe an extensive observational project that has obtained high-quality and homogeneous photometry for a number of different Galactic star clusters (including M 92, M 13, M 3, M 71, and NGC 6791) spanning a wide range in metallicity (−2.3 ≲ [Fe/H] ≲ +0.4), as observed in the u ' g ' r ' i ' z ' passbands with the MegaCam wide-field imager on the Canada–France–Hawaii Telescope. By employing these purest of stellar populations, fiducial sequences have been defined from color–magnitude diagrams that extend from the tip of the red-giant branch down to approximately four magnitudes below the turnoff: these sequences have been accurately calibrated to the standard u ' g ' r ' i ' z ' system via a set of secondary photometric standards located within these same clusters. Consequently, they can serve as a valuable set of empirical fiducials for the interpretation of stellar populations data in the u ' g ' r ' i ' z ' system.
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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 | 0.004 |
| 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 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.028 | 0.012 |
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".