THE NEXT GENERATION VIRGO CLUSTER SURVEY (NGVS). XXV. FIDUCIAL PANCHROMATIC COLORS OF VIRGO CORE GLOBULAR CLUSTERS AND THEIR COMPARISON TO MODEL PREDICTIONS
Bibliographic record
Abstract
ABSTRACT The central region of the Virgo Cluster of galaxies contains thousands of globular clusters (GCs), an order of magnitude more than the number of clusters found in the Local Group. Relics of early star formation epochs in the universe, these GCs also provide ideal targets to test our understanding of the spectral energy distributions (SEDs) of old stellar populations. Based on photometric data from the Next Generation Virgo Cluster Survey (NGVS) and its near-infrared counterpart NGVS-IR, we select a robust sample of GCs with excellent photometry and tha span the full range of colors present in the Virgo core. The selection exploits the well-defined locus of GCs in the uiK diagram and the fact that the GCs are marginally resolved in the images. We show that the GCs define a narrow sequence in five-dimensional color space, with limited but real dispersion around the mean sequence. The comparison of these SEDs with the predictions of 11 widely used population synthesis models highlights differences between the models and also shows that no single model adequately matches the data in all colors. We discuss possible causes for some of these discrepancies. Forthcoming papers of this series will examine how best to estimate photometric metallicities in this context, and compare the Virgo GC colors with those in other environments.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".