Measuring the GC luminosity function up to <i>z</i> ~ 0.2
Bibliographic record
Abstract
Abstract Globular clusters (GCs) are stellar systems (~106 M⊙) with very regular symmetry, single age, and single metallicity. Spectroscopic studies have revealed very old ages, suggesting that GCs were formed in the earliest stages of galaxy formation and assembly. The aim of this work is to find out how far we can measure the GC luminosity function, specific frequency, and radial distribution, applying the surface-brightness-fluctuations (SBF) technique to deep ACS images. To this end, we apply the effects caused by higher redshift to HST/ACS images (in two optical bands, F606W and F814W) of M87, an elliptical galaxy with a very well-studied GC system. The effects involved are: (i) evolution, (ii) inverse k correction, (iii) binning of the image to smaller angular size, (iv) cosmological dimming of surface brightness, and (v) noise addition to account for different exposure times. After processing the images we detect the brightest GCs through direct photometry (e.g., with SExtractor), whereas the unresolved clusters are measured through SBFs. The above treatment is repeated for z=0.05, 0.1, 0.14, and 0.18, and the results are compared to the measurements at z=0 to estimate biases and incompleteness.
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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) | 0.002 | 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".