Wide-Field Survey of Globular Clusters in M31. I. A Catalog of New Clusters
Bibliographic record
Abstract
We present the result of a wide-field survey of globular clusters (GCs) in M31 covering a 3° × 3° field centered on M31. We have searched for GCs on CCD images taken with Washington CMT 1 filters at the KPNO 0.9 m telescope using the following steps: (1) inspection of morphological parameters given by the SExtractor package such as stellarity, full width at half-maximum, and ellipticity; (2) consulting the spectral types and radial velocities obtained from spectra taken with the Hydra spectrograph at the WIYN 3.5 m telescope; and (3) visual inspection of the images of each object. We have found 1164 GCs and GC candidates, of which 605 are newly found GCs and GC candidates and 559 are previously known GCs. Among the new objects there are 113 genuine GCs, 258 probable GCs, and 234 possible GCs, according to our classification criteria. Among the known objects there are 383 genuine GCs, 109 probable GCs, and 67 possible GCs. In total there are 496 genuine GCs, 367 probable GCs, and 301 possible GCs. Most of these newly found GCs have T 1 magnitudes of 17.5-19.5 mag [17.9 < V < 19.9 mag assuming ( C - T 1 ) ≈ 1.5], and ( C - T 1 ) colors in the range 1-2.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".