An environment-dependent halo mass function as a driver for the early quenching of <i>z</i> ≥ 1.5 cluster galaxies
Bibliographic record
Abstract
ABSTRACT Many z ≈1.5 galaxies with a stellar mass (M⋆) $\ge 10^{10}\, \mathrm{M}_\odot$ are already quenched in both galaxy clusters (>50 per cent) and the field (>20 per cent), with clusters having a higher quenched fraction at all stellar masses compared to the field. A puzzling issue is that these massive quenched galaxies have stellar populations of similar age in both clusters and the field. This suggests that, despite the higher quenched fraction in clusters, the dominant quenching mechanism for massive galaxies is similar in both environments. In this work, we use data from the cosmological hydrodynamic simulations Hydrangea and EAGLE to test whether the excess quenched fraction of massive galaxies in z=1.5 clusters results from fundamental differences in their halo properties compared to the field. We find that (i) at $10^{10}\le \, M_{\star }/\mathrm{M}_\odot \, \le 10^{11}$, quenched fractions at 1.5
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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 | 0.000 | 0.000 |
| 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) | 0.002 | 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".