Multiwavelength Mass Comparisons of the \documentclass{aastex} \usepackage{amsbsy} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{bm} \usepackage{mathrsfs} \usepackage{pifont} \usepackage{stmaryrd} \usepackage{textcomp} \usepackage{portland,xspace} \usepackage{amsmath,amsxtra} \usepackage[OT2,OT1]{fontenc} \newcommand\cyr{ \renewcommand\rmdefault{wncyr} \renewcommand\sfdefault{wncyss} \renewcommand\encodingdefault{OT2} \normalfont \selectfont} \DeclareTextFontCommand{\textcyr}{\cyr} \pagestyle{empty} \DeclareMathSizes{10}{9}{7}{6} \begin{document} \landscape $z\sim 0.3$ \end{document} CNOC Cluster Sample
Bibliographic record
Abstract
Results are presented from a detailed analysis of optical and X-ray observations of moderate-redshift galaxy clusters from the Canadian Network for Observational Cosmology (CNOC) subsample of the EMSS. The combination of extensive optical and deep X-ray observations of these clusters make them ideal candidates for multiwavelength mass comparison studies. X-ray surface brightness profiles of 14 clusters with 0.17 < z < 0.55 are constructed from Chandra observations and fit to single- and double-β models. Spatially resolved temperature analysis is performed, indicating that five of the clusters in this sample exhibit temperature gradients within their inner 60-200 kpc. Integrated spectra extracted within R 2500 provide temperature, abundance, and luminosity information. Under assumptions of hydrostatic equilibrium and spherical symmetry, we derive gas and total masses within R 2500 and R 200 . We find an average gas mass fraction of f gas ( R 200 ) = 0.092 ± 0.004 h , resulting in Ω m = 0.42 ± 0.02 (formal error). We also derive dynamical masses for these clusters to R 200 . We find no systematic bias between X-ray and dynamical methods across the sample, with an average M dyn / M X = 0.97 ± 0.05. We also compare X-ray masses to weak-lensing mass estimates of a subset of our sample, resulting in a weighted average of M lens / M X of 0.99 ± 0.07. We investigate X-ray-scaling relationships and find power-law slopes that are slightly steeper than the predictions of self-similar models, with an E ( z ) -1 L X - T X slope of 2.4 ± 0.2 and an E ( z ) M 2500 - T X slope of 1.7 ± 0.1. Relationships between red-sequence optical richness ( B gc,red ) and global cluster X-ray properties ( T X , L X , and M 2500 ) are also examined and fitted.
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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 | 0.002 | 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) | 0.021 | 0.004 |
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".