<i>Chandra</i>X‐Ray Observations of the 0.6 <<i>z</i>< 1.1 Red‐Sequence Cluster Survey Sample
Bibliographic record
Abstract
We present the results of Chandra observations of 13 optically selected clusters with 0.6 < z < 1.1, discovered via the Red-Sequence Cluster Survey (RCS). All but one are detected at S/N > 3, although three were not observed long enough to support detailed analysis. Surface brightness profiles are fitted to β models. Integrated spectra are extracted within R 2500 , and T X and L X information is obtained. We derive gas masses and total masses within R 2500 and R 500 . Cosmologically corrected scaling relations are investigated, and we find the RCS clusters to be consistent with self-similar scaling expectations. However, discrepancies exist between the RCS sample and lower z X-ray-selected samples for relationships involving L X , with the higher z RCS clusters having lower L X for a given T X . In addition, we find that gas mass fractions within R 2500 for the high- z RCS sample are lower than expected by a factor of ~2. This suggests that the central entropy of these high- z objects has been elevated by processes such as preheating, mergers, and/or AGN outbursts, that their gas is still infalling, or that they contain comparatively more baryonic matter in the form of stars. Finally, relationships between red-sequence optical richness ( B gc,red ) and X-ray properties are fitted to the data. For systems with measured T X , we find that optical richness correlates with both T X and mass, having a scatter of ~30% with mass for both X-ray-selected and optically selected clusters. However, we also find that X-ray luminosity is not well correlated with richness and that several of our sample members appear to be significantly X-ray faint.
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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 | 0.000 |
| 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) | 0.002 | 0.001 |
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".