Preprint typeset using L ATEX style emulateapj v. 12/01/06 NEAR-INFRARED PROPERTIES OF MODERATE-REDSHIFT GALAXY CLUSTERS: LUMINOSITY FUNCTIONS AND DENSITY PROFILES
Bibliographic record
Abstract
We present K-band imaging for 15 of the Canadian Network for Observational Cosmology (CNOC1) clusters. The extensive spectroscopic dataset available for these clusters allows us to determine the cluster K-band luminosity function and density profile without the need for statistical background subtraction. The luminosity density and number density profiles can be described by NFW models with concentration parameters of cl = 4.28 ± 0.70 and cg = 4.13 ± 0.57 respectively. Comparing these to the dynamical mass analysis of the same clusters shows that the galaxy luminosity and number density profiles are similar to the dark matter profile, and are not less concentrated like in local clusters. The luminosity functions show that the evolution of K ∗ over the redshift range 0.2 < z < 0.5 is consistent with a scenario where the majority of stars in cluster galaxies form at high-redshift (zf> 1.5) and evolve passively thereafter. The best-fit for the faint-end slope of the luminosity function is α =-0.84 ± 0.08, which indicates that it does not evolve between z = 0 and z = 0.3. Using Principal Component Analysis of the spectra we classify cluster galaxies as either starforming/recently-star-forming (EM+BAL) or non-starforming (ELL) and compute their respective luminosity functions. The faint-end slope of the ELL luminosity function is much shallower than for
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.637 | 0.596 |
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".