Angular clustering of z ∼ 2 star-forming and passive galaxies in 2.5 square degrees of deep CFHT imaging
Bibliographic record
Abstract
We study the angular clustering of z ∼ 2 galaxies using ∼40 000 star-forming (SF) and ∼5000 passively evolving (PE) galaxies selected from ∼2.5 deg2 of deep (Klim = 23–24 AB) Canada–France–Hawaii Telescope imaging. For both populations, the clustering is stronger for galaxies brighter in rest-frame optical and the trend is particularly strong for PE galaxies, indicating that passive galaxies with larger stellar masses reside in more massive haloes. In contrast, at rest-frame ultraviolet we find that while the clustering of SF galaxies increases with increasing luminosity, it decreases for PE galaxies; a possible explanation lies in quenching of star formation in the most massive haloes. Furthermore, we find two components in the correlation functions for both SF and PE galaxies, attributable to one- and two-halo terms. The presence of one-halo terms for both PE and SF galaxies suggests that environmental effects were producing passive galaxies in virtualized environments already by z ∼ 2. Finally, we find notable clustering differences between the four widely separated fields in our study; the popular COSMOS field is the most discrepant (as is also the case for number counts and luminosity functions), highlighting the need for very large areas and multiple sightlines in galaxy evolution statistical studies.
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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 | 0.001 |
| 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".