<b>The</b> EDGE-CALIFA survey: self-regulation of star formation at kpc scales
Bibliographic record
Abstract
ABSTRACT The processes that regulate star formation are essential to understand how galaxies evolve. We present the relation between star formation rate density, ΣSFR , and hydrostatic mid-plane pressure,Ph, for 4260 star-forming regions of kpc size located in 96 galaxies included in the EDGE-CALIFA survey covering a wide range of stellar masses and morphologies. We find that these two parameters are tightly correlated, showing a smaller scatter in comparison to other star-forming relations. A power law, with a slightly sublinear index, is a good representation of this relation. Its residuals show a significant anticorrelation with both stellar age and metallicity whereas the total stellar mass may also play a secondary role in shaping the ΣSFR–Ph relation. For actively star-forming regions, we find that the effective feedback momentum per unit stellar mass (p*/m*), measured from thePh/ΣSFR ratio increases withPh. The median value of this ratio for all the sampled regions is larger than the expected momentum just from supernovae explosions. Morphology of the galaxies, including bars, does not seem to have a significant impact in the ΣSFR–Ph relation. Our analysis indicates that local ΣSFR self-regulation comes mainly from momentum injection to the interstellar medium from supernovae explosions. However, other mechanisms in disc galaxies may also play a significant role in shaping the ΣSFR at kpc scales. Our results also suggest thatPh is the main parameter that modulates star formation at kpc scales, rather than individual components of the baryonic mass.
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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 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".