STAR FORMATION HISTORIES IN A CLUSTER ENVIRONMENT AT<i>z</i>∼ 0.84
Bibliographic record
Abstract
We present a spectrophotometric analysis of galaxies belonging to the dynamically young, massive cluster RX J0152.7−1357 at z ∼ 0.84, aimed at understanding the effects of the cluster environment on the star formation history (SFH) of cluster galaxies and the assembly of the red sequence (RS). We use VLT/FORS spectroscopy, ACS/WFC optical, and NTT/SofI near-IR data to characterize SFHs as a function of color, luminosity, morphology, stellar mass, and local environment from a sample of 134 spectroscopic members. In order to increase the signal-to-noise ratio, individual galaxy spectra are stacked according to these properties. Moreover, the D4000, Balmer, CN3883, Fe4383, and C4668 indices are also quantified. The SFH analysis shows that galaxies in the blue faint-end of the RS have on average younger stars (Δ t ∼ 2 Gyr) than those in the red bright-end. We also found, for a given luminosity range, differences in age (Δ t ∼ 0.5−1.3 Gyr) as a function of color, indicating that the intrinsic scatter of the RS may be due to age variations. Passive galaxies in the blue faint-end of the RS are preferentially located in the low density areas of the cluster, likely being objects entering the RS from the "blue cloud." It is likely that the quenching of the star formation of these RS galaxies is due to interaction with the intracluster medium. Furthermore, the SFH of galaxies in the RS as a function of stellar mass reveals signatures of "downsizing" in the overall cluster.
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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 | 0.001 | 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) | 0.004 | 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".