Different regulation of stellar metallicities between star-forming and quiescent galaxies – insights into galaxy quenching
Bibliographic record
Abstract
ABSTRACT One of the most important questions in astrophysics is what causes galaxies to stop forming stars. Previous studies have shown a tight link between quiescence and black hole mass. Other studies have revealed that quiescence is also associated with ‘starvation’, the halting of gas inflows, which results in the remaining gas being used up by star formation and in rapid chemical enrichment. In this work, we find the missing link between these two findings. Using a large sample of galaxies, we uncover the intrinsic dependences of the stellar metallicity on galaxy properties. In the case of star-forming galaxies, stellar metallicity is primarily driven by stellar mass. However, for passive galaxies, the stellar metallicity is primarily driven by the stellar velocity dispersion. The latter is known to be tightly correlated with black hole mass. This result can be seen as connecting previous studies, where the integrated effect of black hole feedback (i.e. black hole mass, traced by the velocity dispersion) prevents gas inflows, starving the galaxy, which is seen by the rapid increase in the stellar metallicity, and leading to the galaxy becoming passive.
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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 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.002 | 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".