The cold gas and dust properties of red star-forming galaxies
Bibliographic record
Abstract
ABSTRACT We study the cold gas and dust properties for a sample of red star-forming galaxies called ‘red misfits.’ We collect single-dish CO observations and H i observations from representative samples of low-redshift galaxies, as well as our own James Clerk Maxwell Telescope CO observations of red misfits. We also obtain SCUBA-2 850 $\mu$m observations for a subset of these galaxies. With these data we compare the molecular gas, total cold gas, and dust properties of red misfits against those of their blue counterparts (‘blue actives’) taking non-detections into account using a survival analysis technique. We compare these properties at fixed position in the log SFR–log M⋆ plane, as well as versus offset from the star-forming main sequence. Compared to blue actives, red misfits have slightly longer molecular gas depletion times, similar total gas depletion times, significantly lower molecular- and total-gas mass fractions, lower dust-to-stellar mass ratios, similar dust-to-gas ratios, and a significantly flatter slope in the log Mmol–log M⋆ plane. Our results suggest that red misfits as a population are likely quenching due to a shortage in gas supply.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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".