Hidden Cooling Flows in clusters of Galaxies II: a wider sample
Bibliographic record
Abstract
ABSTRACT We have recently uncovered Hidden Cooling Flows (HCFs) in the XMM Reflection Grating Spectrometer spectra of three clusters of galaxies; Centaurus, Perseus, and A1835. Here, we search for them in a wider sample of objects: the X-ray brightest group NGC 5044; four moderate X-ray luminosity clusters Sersic 159, A262, A2052, and RX J0821; and three high X-ray luminosity clusters RX J1532, MACS 1931, and the Phoenix cluster. Finally, we examine two Virgo elliptical galaxies, M49 and M84. All statistically allow the addition of an HCF. We find a significant detection of an HCF in six clusters and two elliptical galaxies. The hidden mass cooling rates are $5{\!-\!}40\hbox{$\hbox{$\rm \, {\rm M}_{\odot }$}{\rm \, yr}^{-1}\, $}$ for the normal clusters, $1000\hbox{$\hbox{$\rm \, {\rm M}_{\odot }$}{\rm \, yr}^{-1}\, $}$ or more for the extreme clusters, and $1{\!-\!}2\hbox{$\hbox{$\rm \, {\rm M}_{\odot }$}{\rm \, yr}^{-1}\, $}$ for the elliptical galaxies. We discuss the implications of the results for the composition of the innermost parts of the massive host galaxies and look forward to future observations.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".