Relations between abundance characteristics and rotation velocity for star-forming MaNGA galaxies
Bibliographic record
Abstract
We derive rotation curves, surface brightness profiles, and oxygen abundance distributions for 147 late-type galaxies using the publicly available spectroscopy obtained by the MaNGA survey. Changes of the central oxygen abundance (O/H)0, the abundance at the optical radius (O/H)R25, and the abundance gradient with rotation velocity Vrot were examined for galaxies with rotation velocities from 90 km s−1 to 350 km s−1. We find that each relation shows a break at $ V_{\mathrm{rot}}^{*} \sim 200 \, {\rm {km\, s}}^{-1}$. The central (O/H)0 abundance increases with rising Vrot and the slope of the (O/H)0–Vrot relation is steeper for galaxies with $ V_{\mathrm{rot}} \lesssim V_{\mathrm{rot}}^{*} $. The mean scatter of the central abundances around this relation is 0.053 dex. The relation between the abundance at the optical radius of a galaxy and its rotation velocity is similar; the mean scatter in abundances around this relation is 0.081 dex. The radial abundance gradient expressed in dex/kpc flattens with the increase of the rotation velocity. The slope of the relation is very low for galaxies with $ V_{\mathrm{rot}} \gtrsim V_{\mathrm{rot}}^{*} $. The abundance gradient expressed in dex/R25 is roughly constant for galaxies with $ V_{\mathrm{rot}} \lesssim V_{\mathrm{rot}}^{*} $, flattens towards $ V_{\mathrm{rot}}^{*} $, and then again is roughly constant for galaxies with $ V_{\mathrm{rot}} \gtrsim V_{\mathrm{rot}}^{*} $. The change of the gradient expressed in terms of dex/hd (where hd is the disc scale length), in terms of dex/Re, d (where Re, d is the disc effective radius), and in terms of dex/Re, g (where Re, g is the galaxy effective radius) with rotation velocity is similar to that for gradient in dex/R25. The relations between abundance characteristics and other basic parameters (stellar mass, luminosity, and radius) are also considered.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".