AGN feedback by relativistic jets
Bibliographic record
Abstract
Abstract Feedback provided by relativistic jets may be effective in shaping the galaxy luminosity function. The quenching mode (quasar mode) at redshifts ~2-3 potentially disperses gas in star-forming galaxies. The maintenance mode (radio mode) heats the gas in galaxy clusters counteracting cooling flows. A number of authors have examined the effect of relativistic jets in dispersing clouds in the kpc-scale inhomogeneous interstellar medium of evolving galaxies. We have also investigated a particular case of maintenance-mode feedback in our simulation of the iconic radio galaxy / cooling flow cluster Hydra A. Modelling of the knots produced by the jets in the inner 10 kpc provides an estimate of 0.8 – 0.9 c for the velocities of the jets in agreement with other velocity estimates for FR1 jets. The addition of jet precession provides realistic simulations of the morphology of the Hydra A radio source and raises interesting questions as to the role of black hole and disk precession, in general, in galaxy formation.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".