Near-infrared properties of metal-poor globular clusters in the Galactic bulge direction
Bibliographic record
Abstract
Aims. J, H, and images obtained from the near-infrared imager CFHTIR on the Canada-France-Hawaii Telescope are used to derive the morphological parameters of the red giant branch (RGB) in the near-infrared color-magnitude diagrams for 12 metal-poor globular clusters in the Galactic bulge direction. Using the compiled data set of the RGB parameters for the observed 12 clusters, in addition to the previously studied 5 clusters, we discuss the properties of the RGB morphology for the clusters and compare them with the calibration relations for the metal-rich bulge clusters and the metal-poor halo clusters. Methods. The photometric RGB shape indices, such as colors at fixed magnitudes of MK = MH = (-5.5, -5, -4, and -3), magnitudes at fixed colors of (J-K = (J-H = 0.7, and the RGB slope, were measured from the fiducial normal points defined in the near-infrared color–magnitude diagrams for each cluster. The magnitudes of RGB bump and tip were also estimated from the differential and cumulative luminosity functions of the selected RGB stars. The derived RGB parameters were used to examine the overall behaviors of the RGB morphology as a function of cluster metallicity.Results. The correlations between the near-infrared photometric RGB shape indices and the cluster metallicity for the program clusters compare favorably with the previous observational calibration relations for metal-rich clusters in the Galactic bulge and the metal-poor halo clusters. The observed near-infrared magnitudes of the RGB bump and tip for the investigated clusters also accord with the previous calibration relations for the Galactic bulge clusters.
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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 | 0.000 |
| 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".