Two growing modes and the morphology–quiescence relation in isolated galaxies
Bibliographic record
Abstract
Quiescence in galaxies correlates strongly with the central density/morphology of the stellar distribution. We investigate two possible explanations for this morphology-quiescence relation: 1) the central density results from a dissipative core-building event ("compaction") that feeds an AGN that quenches the galaxy and 2) the central density results from inside-out growth by galaxy-wide star formation that is quenched by processes unrelated to the central density. We aim to distinguish these two scenarios using the MaNGA survey to determine profiles of stellar age, specific star formation rate (sSFR) and gas phase metallicity (O/H) as a function of stellar mass surface density within 1 kpc (Sigma_1kpc) and total stellar mass (M*). We find that gradients in age, sSFR and O/H depend on the galaxy's position on the Sigma_1kpc-M* diagram, suggesting at least two evolutionary pathways. The first pathway consists of galaxies with low Sigma_1kpc for their M* whose centres are old, metal-rich and suppressed in sSFR compared to their outskirts, consistent with the inside-out growth scenario. The second pathway, consistent with a compaction-like core-building scenario, consists of galaxies with higher Sigma_1kpc for their M*, whose centres are younger, enhanced in sSFR and metal-deficient compared to their outskirts. Moreover, the WISE-selected AGN fraction peaks in the same area of the Sigma_1kpc-M* diagram as the core-building pathway. The sSFR profiles of the quiescent population suggest that galaxies on the compaction-like path quench uniformly, while those on the inside-out growing path quench their centres first. Our results imply that both pathways contribute to the morphology-quiescence relation.
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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 | 0.003 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".