Tracing the Evolution of Specially-resolved Gas and Star Formation Properties Along the Offset from the Star-forming Main Sequence
Bibliographic record
Abstract
Quenching of star formation is one of the key drivers of galaxy evolution. We use data taken from the ALMaQUEST survey (ALMA-MaNGA QUEnching and STar formation) to study the change of spatially-resolved molecular gas and star formation properties as galaxies move away from the star-forming main sequence towards the passive regime. In particular, we are interested in investigating where and how star formation quenchs in galaxies. For example, it is the amount of molecular gas (fuel) available to form new stars or the efficiency of molecular gas to form stars that control star formation quenching in nearby galaxies. Our results show that star formation quenching can be driven by various mechanisms, both within a galaxy and between different galaxies. The different drivers of star formation quenching imply diverse evolutionary paths of galaxies. This study, as well as the ALMaQUEST survey, marks a new era of research using ALMA and its extraordinary capability for exploring cold gas properties in extreme environments and galaxy evolution.
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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) | 0.001 | 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".