Do AGN triggering mechanisms vary with radio power? – II. The importance of mergers as a function of radio power and optical luminosity
Bibliographic record
Abstract
ABSTRACT Investigation of the triggering mechanisms of radio active galactic nuclei (radio AGN) is important for improving our general understanding of galaxy evolution. In the first paper in this series, detailed morphological analysis of high-excitation radio galaxies (HERGs) with intermediate radio powers suggested that the importance of triggering via galaxy mergers and interactions increases strongly with AGN radio power and weakly with optical emission-line luminosity. Here, we use an online classification interface to expand our morphological analysis to a much larger sample of 155 active galaxies (3CR radio galaxies, radio-intermediate HERGs, and Type 2 quasars) that covers a broad range in both 1.4 GHz radio power and [O iii] λ5007 emission-line luminosity. All active galaxy samples are found to exhibit excesses in their rates of morphological disturbance relative to 378 stellar-mass- and redshift-matched non-active control galaxies classified randomly and blindly alongside them. These excesses are highest for the 3CR HERGs (4.7σ) and Type 2 quasar hosts (3.9σ), supporting the idea that galaxy mergers provide the dominant triggering mechanism for these subgroups. When the full active galaxy sample is considered, there is clear evidence to suggest that the enhancement in the rate of disturbance relative to the controls increases strongly with [O iii] λ5007 emission-line luminosity but not with 1.4 GHz radio power. Evidence that the dominant AGN host types change from early-type galaxies at high radio powers to late-type galaxies at low radio powers is also found, suggesting that triggering by secular, disc-based processes holds more importance for lower-power radio AGN.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".