The M31 Globular Cluster Luminosity Function
Bibliographic record
Abstract
We combine our compilation of photometry of M31 globular clusters and probable cluster candidates with new near-infrared photometry for 30 objects. Using these data we determine the globular cluster luminosity function (GCLF) in multiple filters for the M31 halo clusters. We find a GCLF peak and dispersion V = 16.84 ± 0.11, σ t = 0.93 ± 0.13 (Gaussian σ = 1.20 ± 0.14), consistent with previous results. The halo GCLF peak colors (e.g., B - V ) are consistent with the average cluster colors. We also measure V -band GCLF parameters for several other subsamples of the M31 globular cluster population. The inner third of the clusters have a GCLF peak significantly brighter than that of the outer clusters (Δ V 0 ≈ 0.5 mag). Dividing the sample by both galactocentric distance and metallicity, we find that the GCLF also varies with metallicity, as the metal-poor clusters are on average 0.36 mag fainter than the metal-rich clusters. Our modeling of the catalog selection effects suggests that they are not the cause of the measured GCLF differences, but a more complete, less contaminated M31 cluster catalog is required for confirmation. Our results imply that dynamical destruction is not the only factor causing variation in the M31 GCLF: metallicity, age, and cluster initial mass function may also be important.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| 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) | 0.003 | 0.002 |
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".