P-MaNGA: GRADIENTS IN RECENT STAR FORMATION HISTORIES AS DIAGNOSTICS FOR GALAXY GROWTH AND DEATH
Bibliographic record
Abstract
We present an analysis of the data produced by the MaNGA prototype run (P-MaNGA), aiming to test how the radial gradients in recent star formation histories, as indicated by the 4000 Å break (D n (4000)), H δ absorption (EW(H δ A )), and H α emission (EW(H α )) indices, can be useful for understanding disk growth and star formation cessation in local galaxies. We classify 12 galaxies observed on two P-MaNGA plates as either centrally quiescent (CQ) or centrally star-forming (CSF), according to whether D n (4000) measured in the central spaxel of each datacube exceeds 1.6. For each spaxel we generate both 2D maps and radial profiles of D n (4000), EW(H δ A ), and EW(H α ). We find that CSF galaxies generally show very weak or no radial variation in these diagnostics. In contrast, CQ galaxies present significant radial gradients, in the sense that D n (4000) decreases, while both EW(H δ A ) and EW(H α ) increase from the galactic center outward. The outer regions of the galaxies show greater scatter on diagrams relating the three parameters than their central parts. In particular, the clear separation between centrally measured quiescent and star-forming galaxies in these diagnostic planes is largely filled in by the outer parts of galaxies whose global colors place them in the green valley, supporting the idea that the green valley represents a transition between blue-cloud and red-sequence phases, at least in our small sample. These results are consistent with a picture in which the cessation of star formation propagates from the center of a galaxy outward as it moves to the red sequence.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".