A morphological study of galaxies in ZwCl0024+1652, a galaxy cluster at redshift z ∼ 0.4
Bibliographic record
Abstract
Abstract The well-known cluster of galaxies ZwCl0024+1652 at z ∼ 0.4 lacks an in-depth morphological classification of its central region. While previous studies provide a visual classification of a patched area, we used the public code called galaxy Support Vector Machine (galsvm) and HST/ACS data as well as the WFP2 master catalogue to automatically classify all cluster members up to 1 Mpc. galsvm analyses galaxy morphologies through support vector machine (SVM). From the 231 cluster galaxies, we classified 97 as early types (ETs) and 83 as late types (LTs). The remaining 51 stayed unclassified (or undecided). By cross-matching our results with the existing visual classification, we found an agreement of 81 per cent. In addition to previous Zwcl0024 morphological classifications, 121 of our galaxies were classified for the first time in this work. In addition, we tested the location of classified galaxies on the standard morphological diagrams, colour–colour and colour–magnitude diagrams. Out of all cluster members, ∼20 per cent are emission-line galaxies, taking into account previous GLACE results. We have verified that the ET fraction is slightly higher near the cluster core and decreases with the clustercentric distance, while the opposite trend has been observed for LT galaxies. We found a higher fraction of ETs (54 per cent) than LTs (46 per cent) throughout the analysed central region, as expected. In addition, we analysed the correlation between the five morphological parameters (Abraham concentration, Bershady–Concelice concentration, asymmetry, Gini, and M20 moment of light) and the clustercentric distance, without finding a clear trend. Finally, as a result of our work, the morphological catalogue of 231 galaxies containing all the measured parameters and the final classification is available in the electronic form of this paper.
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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 | 0.004 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".