The origin of radio emission in broad absorption line quasars: Results from the LOFAR Two-metre Sky Survey
Bibliographic record
Abstract
We present a study of the low-frequency radio properties of broad absorption line quasars (BALQSOs) from the LOFAR Two-metre Sky-Survey Data Release 1 (LDR1). The value-added LDR1 catalogue contains Pan-STARRS counterparts, which we match with the Sloan Digital Sky Survey (SDSS) DR7 and DR12 quasar catalogues. We find that BALQSOs are twice as likely to be detected at 144 MHz than their non-BAL counterparts, and BALQSOs with low-ionisation species present in their spectra are three times more likely to be detected than those with only high-ionisation species. The BALQSO fraction at 144 MHz is constant with increasing radio luminosity, which is inconsistent with previous results at 1.4 GHz, indicating that observations at the different frequencies may be tracing different sources of radio emission. We cross-match radio sources between the Faint Images of the Radio Sky at Twenty Centimeters (FIRST) survey and LDR1, which provides a bridge via the LDR1 Pan-STARRS counterparts to identify BALQSOs in SDSS. Consequently we expand the sample of BALQSOs detected in FIRST by a factor of three. The LDR1-detected BALQSOs in our sample are almost exclusively radio-quiet (log( R 144 MHz ) < 2), with radio sizes at 144 MHz typically less than 200 kpc; these radio sizes tend to be larger than those at 1.4 GHz, suggesting more extended radio emission at low frequencies. We find that although the radio detection fraction increases with increasing balnicity index (BI), there is no correlation between BI and either low-frequency radio power or radio-loudness. This suggests that both radio emission and BI may be linked to the same underlying process, but are spatially distinct phenomena.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| 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) | 0.001 | 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".