A comprehensive radio study of narrow-line Seyfert 1 galaxies
Bibliographic record
Abstract
Narrow-line Seyfert 1 (NLS1) galaxies are a type of active galactic nuclei (AGNs) that had originally been classified as sources with little to no radio emission. Although the class is rather unified from an optical perspective, their radio characteristics are diverse. One of the most curious aspects of these sources is their ability to form and maintain powerful relativistic jets. In this work, we studied the radio properties of the cleanest available sample of 3998 NLS1 galaxies, which allowed us to investigate the population-wide characteristics. We used both historical and ongoing surveys: LOw-Frequency ARray (LOFAR) Two-metre Sky Survey (LoTSS; 144 MHz), Faint Images of the Radio Sky at Twenty-centimeters (FIRST; 1.4 GHz), National Radio Astronomy Observatory (NRAO) Very Large Array (VLA) Sky Survey (NVSS; 1.4 GHz), and VLA Sky Survey (VLASS; 3 GHz). We were able to obtain a radio detection for ∼40% of our sources, with the largest number of detections provided by LoTSS. The majority of the detected NLS1 galaxies are faint (∼1 − 2 mJy) and non-variable, suggesting considerable contributions from star formation activities, especially at 144 MHz. However, we identified samples of extreme sources, for example, in fractional variability and radio luminosity, indicating significant AGN activity. Our results highlight the heterogeneity of the NLS1 galaxy population in radio, laying the foundation for targeted future studies.
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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 | 0.000 | 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".