The morphological transformation of red sequence galaxies in the distant cluster XMMU J1229+0151
Bibliographic record
Abstract
We present the results of a detailed analysis of galaxy properties along the red sequence in XMMU J1229+0151, an X-ray selected cluster at z = 0.98 drawn from the High Acuity Wide field K-band Imager Cluster Survey. Taking advantage of the broad photometric coverage and the availability of 77 spectra in the cluster field, we fit synthetic spectral energy distributions, and estimate stellar masses and photometric redshifts, which we use to determine the cluster membership. We investigate morphological and structural properties of red sequence galaxies and find that elliptical galaxies populate the bright end, while S0 galaxies represent the predominant population at intermediate luminosities, with their fraction decreasing at fainter magnitudes. A comparison with the low-redshift sample of the Wide Field Nearby Galaxy-clusters Survey cluster survey reveals that at z ∼ 1 the bright end of the red sequence of XMMU J1229+0151 is richer in S0 galaxies. The faint end of the red sequence in XMMU J1229+0151 appears rich in disc-dominated galaxies, which are rarer in the low-redshift comparison sample at the same luminosities. Despite these differences between the morphological composition of the red sequence in XMMU J1229+0151 and in low-redshift samples, we find that to within the uncertainties, no such difference exists in the ratio of luminous to faint galaxies along the red sequence.
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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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".