The baryon budget on the galaxy group/cluster boundary
Bibliographic record
Abstract
We present a study of the hot gas and stellar content of five optically selected poor galaxy clusters, including a full accounting of the contribution from intracluster light (ICL) and a combined hot gas and hydrostatic X-ray mass analysis with XMM–Newton observations. We find weighted mean stellar (including ICL), gas and total baryon mass fractions within r500 of 0.026 ± 0.003, 0.070 ± 0.005 and 0.096 ± 0.006, respectively, at a corresponding weighted mean M500 of (1.08+ 0.21− 0.18) × 1014 M⊙. Even when accounting for the intracluster stars, four out of five clusters show evidence for a substantial baryon deficit within r500, with baryon fractions (fb) between 50 ± 6 and 59 ± 8 per cent of the universal mean level (i.e. Ωb/Ωm), the remaining cluster having fb = 75±11 per cent. For the three clusters where we can trace the hot halo to r500 we find no evidence for a steepening of the gas density profile in the outskirts with respect to a power law, as seen in more massive clusters. We find that in all cases, the X-ray mass measurements are larger than those originally published on the basis of the galaxy velocity dispersion (σ) and an assumed σ-M500 relation, by a factor of 1.7–5.7. Despite these increased masses, the stellar fractions (in the range 0.016–0.034, within r500) remain consistent with the trend with mass published by Gonzalez et al., from which our sample is drawn.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.003 | 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".