SDSS-ALMA Legacy Value Archival Gas Exploration (SALVAGE) – I. Global star formation is governed by central (not global) molecular gas
Bibliographic record
Abstract
ABSTRACT Star-forming galaxies form tight relations between their stellar mass, star formation rate, and molecular gas reservoir on global and resolved scales. On the path to quiescence, the exchange between gas and stars must inevitably be broken. Understanding the mechanisms governing star formation and quenching therefore requires observations of both the stellar and molecular gas components. To this end, we have assembled a sample of 277 galaxies ($0.02 \lesssim z \lesssim 0.25$) with semiresolved optical and millimetre $^{12}$CO (1–0) data, wherein the properties of the inner $\sim$2 kpc can be distinguished from the outer regions. This effort was made possible by the Sloan Digital Sky Survey (SDSS) catalogues and the maturing archive of the Atacama Large (sub-)Millimetre Array (ALMA). We call this data set the SDSS-ALMA Legacy-Value Archival Gas Exploration (SALVAGE). In this work, we leverage SALVAGE to provide a semiresolved perspective on global scaling relations and why some galaxies deviate from them. In agreement with previous work, we find that the offset of a galaxy from the global star-forming main sequence (SFMS) is driven by its inner star formation rate. With the relative inner and outer distributions of molecular gas fraction and star formation efficiency, we investigate whether the central star formation driving global changes is due to fuel availability or efficiency. We find that the position of a galaxy within the SFMS is largely due to the inner star formation efficiency, while departure from the SFMS is driven by availability of central gas. The central few kpc are thus the most consequential region for galaxy evolution at low redshift.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".