Post-starburst galaxies in SDSS-IV MaNGA
Bibliographic record
Abstract
ABSTRACT Post-starburst galaxies, identified by their unusually strong Balmer absorption lines and weaker than average emission lines, have traditionally been selected based on their central stellar populations. Here we identify 360 galaxies with post-starburst regions from the MaNGA integral field survey and classify these galaxies into three types: 31 galaxies with central post-starburst regions (CPSB), 37 galaxies with off-centre ring-like post-starburst regions (RPSB), and 292 galaxies with irregular post-starburst regions (IPSB). Focusing on the CPSB and RPSB samples, and comparing their radial gradients in Dn4000, HδA, and W(H α) to control samples, we find that while the CPSBs have suppressed star formation throughout their bulge and disc, and there is clear evidence of rapid decline of star formation in the central regions, the RPSBs only show clear evidence of recently rapidly suppressed star formation in their outer regions and an ongoing central starburst. The radial profiles in mass-weighted age and stellar v/σ indicate that CPSBs and RPSBs are not simply different evolutionary stages of the same event, rather the CPSB galaxies are caused by a significant disruptive event, while the RPSB galaxies are caused by disruption of gas fuelling to the outer regions. Compared to the control samples, both CPSB and RPSB galaxies show a higher fraction of interactions/mergers, misaligned gas, or bars that might be the cause of the gas inflows and subsequent quenching.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".