STAR FORMATION IN INTERMEDIATE REDSHIFT 0.2 < z < 0.7 BRIGHTEST CLUSTER GALAXIES
Bibliographic record
Abstract
ABSTRACT We present a multi-wavelength photometric and spectroscopic study of 42 Brightest Cluster Galaxies (BCGs) in two samples of galaxy clusters chosen for a gravitational lensing study. The study’s initial sample combines 25 BCGs from the Cluster Lensing and Supernova Survey with Hubble sample and 37 BCGs from the Sloan Giant Arcs Survey with a total redshift range of Using archival GALEX, Hubble Space Telescope, Wide-Field Infrared Survey Explorer, Herschel, and Very Large Array data we determine the BCGs’ stellar mass, radio power, and star formation rates. The radio power is higher than expected if due to star formation, consistent with the BCGs being active galactic nucleus (AGN)-powered radio sources. This suggests that the AGN and star formation are both fueled by cold gas in the host galaxy. The specific star formation rate (sSFR) is low and constant with redshift. The mean sSFR is 9.42 × 10−12 yr−1, which corresponds to a mass doubling time of 105 billion years. These findings are consistent with models for hierarchical formation of BCGs, which suggest that star formation is no longer a significant channel for galaxy growth for z 1. Instead, stellar growth (of the order of a factor of at least two) during this period is expected to occur mainly via minor dry mergers.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".