High radio-frequency properties and variability of brightest cluster galaxies
Bibliographic record
Abstract
We consider the high radio-frequency (15–353 GHz) properties and variability of 35 brightest cluster galaxies (BCGs). These are the most core-dominated sources drawn from a parent sample of more than 700 X-ray selected clusters, thus allowing us to relate our results to the general population. We find that ≥6.0 per cent of our parent sample (≥15.1 per cent if only cool-core clusters are considered) contain a radio source at 150 GHz of at least 3 mJy (≈1×1023 W Hz−1 at our median redshift of z ≈ 0.13). Furthermore, ≥3.4 per cent of the BCGs in our parent sample contain a peaked component (Gigahertz Peaked Spectrum, GPS) in their spectra that peaks above 2 GHz, increasing to ≥8.5 per cent if only cool-core clusters are considered. We see little evidence for strong variability at 15 GHz on short (week–month) time-scales although we see variations greater than 20 per cent at 150 GHz over six-month time frames for 4 of the 23 sources with multi-epoch observations. Much more prevalent is long-term (year–decade time-scale) variability, with average annual amplitude variations greater than 1 per cent at 15 GHz being commonplace. There is a weak trend towards higher variability as the peak of the GPS-like component occurs at higher frequency. We demonstrate the complexity that is seen in the radio spectra of BCGs and discuss the potentially significant implications of these high-peaking components for Sunyaev–Zel‘dovich cluster searches.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".