Time-slicing spiral galaxies with SDSS-IV MaNGA
Bibliographic record
Abstract
ABSTRACT Spectra of galaxies contain a wealth of information about the stellar populations from which they are made. With integral field unit (IFU) surveys, such data can be used to map out stellar population properties across the face of a galaxy, allowing one to go beyond simple radial profiles and study details of non-axisymmetric structure. To-date, however, such studies have been limited by the quality of available data and the power of spectral analysis tools. We now take the next step and study the barred spiral galaxy MCG + 07-28-064 from observations obtained as part of the SDSS-IV MaNGA project. We find that we can decompose this galaxy into ‘time slices,’ which reveal the varying contributions that stars of differing ages make to its bar and spiral structure, offering new insight into the evolution of these features. We find evidence for the ongoing growth of the bar, including the most recent star formation on its leading edge, and for the underlying density wave responsible for spiral structure. This pilot study indicates that there is a wealth of untapped information on the spatial distribution of star formation histories available in the current generation of IFU galaxy surveys.
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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 | 0.002 |
| 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 | 0.001 |
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".