VALES V: a kinematic analysis of the molecular gas content in<i>H</i>-ATLAS galaxies at<i>z</i> ∼ 0.03–0.35 using ALMA
Bibliographic record
Abstract
We present Atacama Large Millimeter/submillimeter Array (ALMA) resolved observations of molecular gas in galaxies up to |$z$| = 0.35 to characterize the role of global galactic dynamics on the global interstellar medium properties. These observations consist of a sub-sample of 39 galaxies taken from the Valparaíso ALMA Line Emission Survey (VALES). From the CO(J = 1–0) emission line, we quantify the kinematic parameters by modelling the velocity fields. We find that the infrared (IR) luminosity increases with the rotational to dispersion velocity ratio (Vrot/σ|$v$|, corrected for inclination). We find a dependence between Vrot/σ|$v$| and the [C ii]/IR ratio, suggesting that the so-called [C ii] deficit is related to the dynamical state of the galaxies. We find that global pressure support is needed to reconcile the dynamical mass estimates with the stellar masses in our systems with low Vrot/σ|$v$| values. The star formation rate (SFR) is weakly correlated with the molecular gas fraction (|$f_{\rm H_2}$|) in our sample, suggesting that the release of gravitational energy from cold gas may not be the main energy source of the turbulent motions seen in the VALES galaxies. By defining a proxy of the ‘star formation efficiency’ (SFE) parameter as the SFR divided by the CO luminosity (SFE′ ≡ SFR/L|$^{\prime }_{\rm CO}$|), we find a constant SFE′ per crossing time (tcross). We suggest that tcross may be the controlling time-scale in which the star formation occurs in dusty |$z$| ∼ 0.03–0.35 galaxies.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 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".