What drives kpc-scale outflows in Radio-Quiet AGN? Insights from a Polarimetric Study
Bibliographic record
Abstract
We present a review of our findings on the origin, drivers, nature, and impact of kiloparsec-scale radio emission in radio-quiet (RQ) AGN. Using radio polarimetric techniques, we probe the dynamics and magnetic (B-) field geometry of outflows in Seyfert and LINER galaxies. Multi-band data from the Karl G. Jansky Very Large Array (VLA) reveal how low-power jets interact with their environment. These interactions can slow down and disrupt the radio outflows while locally regulating star formation through AGN feedback. Several radio properties correlate strongly with the black hole mass, similar to trends observed in radio-loud (RL) AGN. Although their characteristics differ, RQ systems might not be intrinsically distinct from RL AGN, apart from lower jet powers. Our polarization measurements further suggest a composite model in which a black hole-accretion disk system drives both a collimated jet with a small-pitch-angle helical B-field and a wide-angle wind threaded by a high-pitch-angle helical field.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| 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".