The MAVERIC survey: A catalogue of radio sources in southern globular clusters from the Australia Telescope Compact Array
Bibliographic record
Abstract
Radio continuum observations offer a new window on compact objects in globular clusters compared to typical X-ray or optical studies. As part of the MAVERIC survey, we have used the Australia Telescope Compact Array to carry out a deep (median central noise level of approximately 4 microJy per beam) radio continuum survey of 26 southern globular clusters at central frequencies of 5.5 and 9.0 GHz. This paper presents a catalogue of 1285 radio continuum sources in the fields of these 26 clusters. Considering the surface density of background sources, we find significant evidence for a population of radio sources in seven of the 26 clusters, and also identify at least 11 previously known compact objects (6 pulsars and 5 X-ray binaries). While the overall density of radio continuum sources with 7.25-GHz flux densities greater than about 20 microJy in typical globular clusters is relatively low, the survey has already led to the discovery of several exciting compact binaries, including a candidate ultracompact black hole X-ray binary in 47 Tuc. Many of the unclassified radio sources near the centres of the clusters are likely to be true cluster sources, and multi-wavelength follow-up will be necessary to classify these objects and better understand the demographics of accreting compact binaries in globular 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 | 0.002 | 0.002 |
| 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".