Evidence for strong evolution in galaxy environmental quenching efficiency between z = 1.6 and z = 0.9
Why this work is in the frame
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Bibliographic record
Abstract
Abstract We analyse the evolution of environmental quenching efficiency, the fraction of quenched cluster galaxies that would be star-forming if they were in the field, as a function of redshift in 14 spectroscopically confirmed galaxy clusters with 0.87 < $z$ < 1.63 from the Spitzer Adaptation of the Red-Sequence Cluster Survey (SpARCS). The clusters are the richest in the survey at each redshift. Passive fractions rise from $42_{-13}^{+10}$% at $z$ ∼ 1.6 to $80_{-9}^{+12}$% at $z$ ∼ 1.3 and $88_{-3}^{+4}$% at $z$ < 1.1, outpacing the change in passive fraction in the field. Environmental quenching efficiency rises dramatically from $16_{-19}^{+15}$% at $z$ ∼ 1.6 to $62_{-15}^{+21}$% at $z$ ∼ 1.3 and $73_{-7}^{+8}$% at $z$ ≲ 1.1. This work is the first to show direct observational evidence for a rapid increase in the strength of environmental quenching in galaxy clusters at $z$ ∼ 1.5, where simulations show cluster-mass halos undergo non-linear collapse and virialisation.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 it