THE ATACAMA COSMOLOGY TELESCOPE: DETECTION OF SUNYAEV-ZEL'DOVICH DECREMENT IN GROUPS AND CLUSTERS ASSOCIATED WITH LUMINOUS RED GALAXIES
Bibliographic record
Abstract
We present a detection of the Sunyaev–Zel'dovich (SZ) decrement associated with the luminous red galaxy (LRG) sample of the Sloan Digital Sky Survey. The SZ data come from 148 GHz maps of the equatorial region made by the Atacama Cosmology Telescope. The LRG sample is divided by luminosity into four bins, and estimates for the central SZ temperature decrement are calculated through a stacking process. We detect and account for a bias of the SZ signal due to weak radio sources. We use numerical simulations to relate the observed decrement to Y 200 and clustering properties to relate the galaxy luminosity to halo mass. We also use a relation between brightest cluster galaxy luminosity and cluster mass based on stacked gravitational lensing measurements to estimate the characteristic halo masses. The masses are found to be around 10 14 M ☉ .
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".