A comparison of optical and near-infrared colours of Magellanic Cloud star clusters with predictions of simple stellar population models
Bibliographic record
Abstract
Accepted.... Received...; in original form... We present integrated JHKs 2MASS photometry and a compilation of integratedlight optical photoelectric measurements for 84 star clusters in the Magellanic Clouds. These clusters range in age from ≈ 200 Myr to> 10 Gyr, and have [Fe/H] values from −2.2 to −0.1 dex. We find a spread in the intrinsic colours of clusters with similar ages and metallicities, at least some of which is due to stochastic fluctuations in the number of bright stars residing in low-mass clusters. We use 54 clusters with the most reliable age and metallicity estimates as test particles to evaluate the performance of four widely used SSP models in the optical/NIR colour-colour space. All models reproduce the reddening-corrected colours of the old ( � 10 Gyr) globular clusters quite well, but model performance varies at younger ages. In order to account for the effects of stochastic fluctuations in individual clusters, we provide composite B − V, B − J, V − J, V − Ks and J − Ks colours for Magellanic Cloud clusters in several different age intervals. The accumulated mass for most composite clusters are higher
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".