THE ACS VIRGO CLUSTER SURVEY XVI. SELECTION PROCEDURE AND CATALOGS OF GLOBULAR CLUSTER CANDIDATES
Bibliographic record
Abstract
We present catalogs of globular cluster candidates for the 100 galaxies of the Advanced Camera for Surveys Virgo Cluster Survey, a large program to carry out imaging of early-type members of the Virgo Cluster using the Advanced Camera for Surveys (ACS) on the Hubble Space Telescope . We describe the procedure used to select bona fide globular cluster candidates out of the full list of detections based on model-based clustering methods with the use of expected contamination catalogs constructed using blank field observations and which are customized for each galaxy. We also present the catalogs of expected contaminants for each of our target galaxies. For each detected source we measure its position, magnitudes in the F475W (≈ Sloan g ) and F850LP (≈ Sloan z ) bandpasses, and half-light radii by fitting point-spread function convolved King models to the observed light distribution. These measurements are presented for 20,375 sources, of which 12,763 are likely to be globular clusters. Finally, we detail the calculation of the aperture corrections adopted for the globular cluster photometry.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.032 | 0.033 |
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".