The EDGE-CALIFA Survey: The Resolved Star Formation Efficiency and Local Physical Conditions
Bibliographic record
Abstract
Abstract We measure the star formation rate (SFR) per unit gas mass and the star formation efficiency (SFE gas for total gas, SFE mol for the molecular gas) in 81 nearby galaxies selected from the EDGE-CALIFA survey, using 12 CO ( J = 1–0) and optical IFU data. For this analysis we stack CO spectra coherently by using the velocities of H α detections to detect fainter CO emission out to galactocentric radii r gal ∼ 1.2 r 25 (∼3 R e ) and include the effects of metallicity and high surface densities in the CO-to-H 2 conversion. We determine the scale lengths for the molecular and stellar components, finding a close to 1:1 relation between them. This result indicates that CO emission and star formation activity are closely related. We examine the radial dependence of SFE gas on physical parameters such as galactocentric radius, stellar surface density Σ ⋆ , dynamical equilibrium pressure P DE , orbital timescale τ orb , and the Toomre Q stability parameter (including star and gas Q star+gas ). We observe a generally smooth, continuous exponential decline in the SFE gas with r gal . The SFE gas dependence on most of the physical quantities appears to be well described by a power law. Our results also show a flattening in the SFE gas – τ orb relation at log [ τ orb ] ∼ 7.9 – 8.1 and a morphological dependence of the SFE gas per orbital time, which may reflect star formation quenching due to the presence of a bulge component. We do not find a clear correlation between SFE gas and Q star+gas .
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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) | 0.002 | 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".