THE COSMOS-WIRCam NEAR-INFRARED IMAGING SURVEY. I.<i>BzK</i>-SELECTED PASSIVE AND STAR-FORMING GALAXY CANDIDATES AT<i>z</i>≳ 1.4
Bibliographic record
Abstract
We present a new near-infrared survey covering the 2 deg^2 COSMOS field conducted using WIRCam at the Canada-France-Hawaii Telescope. By combining our near-infrared data with Subaru B and z images, we construct a deep, wide-field optical-infrared catalog. At K_s < 23 (AB magnitudes), our survey completeness is greater than 90% and 70% for stars and galaxies, respectively, and contains 143,466 galaxies and 13,254 stars. Using the BzK diagram, we divide our galaxy catalog into quiescent and star-forming galaxy candidates. At z ~ 2, our catalogs contain 3931 quiescent and 25,757 star-forming galaxies representing the largest and most secure sample at these depths and redshifts to date. Our counts of quiescent galaxies turns over at K_s ~ 22, an effect that we demonstrate cannot be due to sample incompleteness. Both the number of faint and bright quiescent objects in our catalogs exceed the predictions of a recent semi-analytic model of galaxy formation, indicating potentially the need for further refinements in the amount of merging and active galactic nucleus feedback at z ~ 2 in these models. We measure the angular correlation function for each sample and find that the slope of the field galaxy correlation function flattens to 1.5 by K_s ~ 23. At small angular scales, the angular correlation function for passive BzK galaxies is considerably in excess of the clustering of dark matter. We use precise 30-band photometric redshifts to derive the spatial correlation length and the redshift distributions for each object class. At K_s < 22, we find r^(γ/1.8)_0 = 7.0 ± 0.5 h^(–1) Mpc for the passive BzK candidates and 4.7 ± 0.8 h^(–1) Mpc for the star-forming BzK galaxies. Our pBzK galaxies have an average photometric redshift of z_p ~ 1.4, in approximate agreement with the limited spectroscopic information currently available. The stacked K_s image will be made publicly available from IRSA.
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How this classification was reachedexpand
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 | 0.003 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".