A comprehensive study of the radio properties of brightest cluster galaxies
Bibliographic record
Abstract
We examine the radio properties of the brightest cluster galaxies (BCGs) in a large sample of X-ray selected galaxy clusters comprising the Brightest Cluster Sample (BCS), the extended BCS and ROSAT-ESO Flux Limited X-ray cluster catalogues. We have multifrequency radio observations of the BCG using a variety of data from the Australia Telescope Compact Array, Jansky Very Large Array and Very Long Baseline Array telescopes. The radio spectral energy distributions of these objects are decomposed into a component attributed to on-going accretion by the active galactic nuclei (AGN) that we refer to as ‘the core’, and a more diffuse, ageing component we refer to as the ‘non-core’. These BCGs are matched to previous studies to determine whether they exhibit emission lines (principally Hα), indicative of the presence of a strong cooling cluster core. We consider how the radio properties of the BCGs vary with cluster environmental factors. Line emitting BCGs are shown to generally host more powerful radio sources, exhibiting the presence of a strong, distinguishable core component in about 60 per cent of cases. This core component more strongly correlates with the BCG's [O iii] 5007 Å line emission. For BCGs in line emitting clusters, the X-ray cavity power correlates with both the extended and core radio emission, suggestive of steady fuelling of the AGN over bubble-rise time-scales in these clusters.
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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 | 0.004 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".