Both stellar mass and gravitational potential shape the gas-phase metallicity
Bibliographic record
Abstract
ABSTRACT The relation between metallicity and galaxy mass (the so-called mass–metallicity relation) is the strongest and most prominent among scaling relations between chemical enrichment and galactic properties. However, it is unclear whether this relation primarily traces metal retention or the integrated production of metals, as past studies have obtained contrasting results. We investigate this issue through an extensive Random Forest and Partial Correlations analysis of spectral cubes of 4500 galaxies from the MaNGA survey. We find that stellar mass ($M_*$) and baryonic gravitational potential ($\Phi _* = M_*/R_\mathrm{ e}$) are the two most important quantities determining gas metallicity in galaxies. However, their relative roles strongly depend on the galactocentric radius – the metallicity within 0.7 $\rm R_e$ depends primarily on the stellar mass, while the metallicity at radii beyond 0.9 $\rm R_e$ depends primarily on the gravitational potential. This finding can be interpreted in terms of metals in the central region ($\rm \mathit{ R}\le 0.7\,R_e$) being mostly bound, regardless of the global gravitational potential and, therefore, the metallicity is determined primarily by the cumulative production of metals (hence the integrated star formation history, i.e. $M_*$); by contrast, in the galactic peripheries the retention of metals depends more critically on the gravitational potential, hence the stronger dependence of the metallicity on $\rm \Phi _*$ at large radii. Our finding reconciles apparent discrepancies between previous results. Finally, we find that the Star Formation Rate is the third most important parameter (after $M_*$ and $\rm \Phi _*$) in determining the metallicity, as expected from the Fundamental Metallicity 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 | 0.002 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".