The EDGE–CALIFA survey: the local and global relations between Σ*, ΣSFR, and Σmol that regulate star formation
Bibliographic record
Abstract
ABSTRACT We present a new characterization of the relations between star-formation rate, stellar mass, and molecular gas mass surface densities at different spatial scales across galaxies (from galaxy-wide to kpc scales). To do so, we make use of the largest sample combining spatially resolved spectroscopic information with CO observations, provided by the Extragalactic Database for Galaxy Evolution (EDGE)–Calar Alto Legacy Integral Field Area (CALIFA) survey, together with new single-dish CO observations obtained by the Atacama Pathfinder Experiment (APEX). We show that these relations are the same at the different scales explored, sharing the same distributions for the explored data, with similar slope, intercept, and scatter (when characterized by a simple power law). From this analysis, we propose that these relations are the projection of a single relation between the three properties that follows a distribution described well by a line in three-dimensional parameter space. Finally, we show that observed secondary relations between the residuals and the parameters considered are explained fully by the correlation between the uncertainties, and therefore have no physical origin. We discuss these results in the context of the hypothesis of self-regulation of the star-formation process.
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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 | 0.001 | 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) | 0.001 | 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".