The ALMaQUEST Survey. XII. Dense Molecular Gas as Traced by HCN and HCO<sup>+</sup> in Green Valley Galaxies
Bibliographic record
Abstract
Abstract We present Atacama Large Millimeter/submillimeter Array (ALMA) observations of two dense gas tracers, HCN (1−0) and HCO + (1-0) for three galaxies in the green valley and two galaxies on the star-forming main sequence with comparable molecular gas fractions as traced by the CO (1−0) emissions, selected from the ALMaQUEST survey. We investigate whether the deficit of molecular gas star formation efficiency (SFE mol ) that leads to the low specific star formation rate (sSFR) in these green valley galaxies is due to a lack of dense gas (characterized by the dense gas fraction f dense ) or the low star formation efficiency of dense gas (SFE dense ). We find that SFE mol as traced by the CO emissions, when considering both star-forming and retired spaxels together, is tightly correlated with SFE dense and depends only weakly on f dense . The sSFR on kiloparsec scales is primarily driven by SFE mol and SFE dense , followed by the dependence on f mol , and is least correlated with f dense or the dense-gas-to-stellar mass ratio ( R dense ). When compared with other works in the literature, we find that our green valley sample shows lower global SFE mol and lower SFE dense while exhibiting similar dense gas fractions when compared to star-forming and starburst galaxies. We conclude that the star formation of the three green valley galaxies with a normal abundance of molecular gas is suppressed, mainly due to the reduced SFE dense rather than the lack of dense 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 | 0.000 |
| 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 | 0.000 | 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".