OPTICAL AND INFRARED PHOTOMETRY OF GLOBULAR CLUSTERS IN NGC 1399: EVIDENCE FOR COLOR-METALLICITY NONLINEARITY
Bibliographic record
Abstract
We combine new Wide Field Camera 3 IR Channel (WFC3/IR) F160W ( H 160 ) imaging data for NGC 1399, the central galaxy in the Fornax cluster, with archival F475W ( g 475 ), F606W ( V 606 ), F814W ( I 814 ), and F850LP ( z 850 ) optical data from the Advanced Camera for Surveys (ACS). The purely optical g 475 − I 814 , V 606 − I 814 , and g 475 − z 850 colors of NGC 1399's rich globular cluster (GC) system exhibit clear bimodality, at least for magnitudes I 814 > 21.5. The optical–IR I 814 − H 160 color distribution appears unimodal, and this impression is confirmed by mixture modeling analysis. The V 606 − H 160 colors show marginal evidence for bimodality, consistent with bimodality in V 606 − I 814 and unimodality in I 814 − H 160 . If bimodality is imposed for I 814 − H 160 with a double Gaussian model, the preferred blue/red split differs from that for optical colors; these "differing bimodalities" mean that the optical and optical–IR colors cannot both be linearly proportional to metallicity. Consistent with the differing color distributions, the dependence of I 814 − H 160 on g 475 − I 814 for the matched GC sample is significantly nonlinear, with an inflection point near the trough in the g 475 − I 814 color distribution; the result is similar for the I 814 − H 160 dependence on g 475 − z 850 colors taken from the ACS Fornax Cluster Survey. These g 475 − z 850 colors have been calibrated empirically against metallicity; applying this calibration yields a continuous, skewed, but single-peaked metallicity distribution. Taken together, these results indicate that nonlinear color–metallicity relations play an important role in shaping the observed bimodal distributions of optical colors in extragalactic GC systems.
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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 | 0.001 | 0.001 |
| 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) | 0.001 | 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".