The EDGE–CALIFA survey: central molecular gas depletion in AGN host galaxies – a smoking gun for quenching?
Bibliographic record
Abstract
ABSTRACT Feedback from an active galactic nucleus (AGN) is often implicated as a mechanism that leads to the quenching of galactic star formation. However, AGN-driven quenching is challenging to reconcile with observations that AGN hosts tend to harbour equal (or even excess) amounts of gas compared with inactive galaxies of similar stellar mass. In this paper, we investigate whether AGN feedback happens on sub-galactic (kpc) scales, an effect that might be difficult to detect with global gas measurements. Using kpc-scale measurements of molecular gas ($\Sigma _{\rm H_2}$) and stellar mass (Σ⋆) surface densities, taken from the Extragalactic Data base for Galaxy Evolution–Calar Alto Legacy Integral Field Area survey, we show that the gas fractions of central AGN regions are typically a factor of ∼ 2 lower than those in star-forming regions. Based on four galaxies with the best spaxel statistics, the difference between AGN and star-forming gas fractions is seen even within a given galaxy, indicating that AGN feedback is able to deplete the molecular gas reservoir in the central few kpc.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".