Atomic gas fractions in active galactic nucleus host galaxies
Bibliographic record
Abstract
The feedback from an active galactic nucleus (AGN) is frequently invoked as a mechanism through which gas can be heated or removed from a galaxy. However, gas fraction measurements in AGN hosts have yielded mixed support for this scenario. Here, we revisit the assessment of fgas (= MHI/M⋆) in z < 0.05 AGN hosts in the Sloan Digital Sky Survey (SDSS) using two complementary techniques. First, we investigate fgas for 75 AGN host galaxies in the extended GALEX Arecibo SDSS Survey (xGASS), whose atomic gas fractions are complete to a few per cent. Second, we construct H i spectral stacks of 1562 AGN from the Arecibo Legacy Fast ALFA (ALFALFA) survey, which enables us to extend the AGN sample to lower stellar masses. Both techniques find that, at fixed M⋆, AGN hosts with log (M⋆/M⊙) ≳ 10.2 are H i rich by a factor of ∼2. However, this gas fraction excess disappears when the control sample is additionally matched in star formation rate (SFR), indicating that these AGN hosts are actually H i normal. At lower stellar mass, the stacking analysis reveals that AGN hosts are H i poor at fixed stellar mass. In the lowest M⋆ regime probed by our sample, 9 < log (M⋆/M⊙) < 9.6, the H i deficit in AGN hosts is a factor of ∼4, and remains at a factor of ∼2 even when the control sample is additionally matched in SFR. Our results help reconcile previously conflicting results, by showing that matching control samples by more than just stellar mass is critical for a rigorous comparison.
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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 | 0.000 |
| Scholarly communication | 0.001 | 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".