VLA Legacy Survey of Molecular Gas in Massive Star-forming Galaxies at High Redshift
Bibliographic record
Abstract
Abstract We present the initial results of an ongoing survey with the Karl G. Jansky Very Large Array targeting the CO(J = 1–0) transition in a sample of 30 submillimeter-selected, dusty star-forming galaxies (SFGs) at z = 2–5 with existing mid-J CO detections from the Atacama Large Millimeter/submillimeter Array and NOrthern Extended Millimeter Array, of which 17 have been fully observed. We detect CO(1–0) emission in 11 targets, along with three tentative (∼1.5σ–2σ) detections; three galaxies are undetected. Our results yield total molecular gas masses of 6–23 × 1010 (α CO/1) M ⊙, with gas mass fractions, f gas = M mol/(M *+M mol), of 0.1–0.8 and a median depletion time of (140 ± 70) Myr. We find median CO excitation ratios of r 31 = 0.75 ± 0.39 and r 41 = 0.63 ± 0.44, with significant scatter. We find no significant correlation between the excitation ratio and a number of key parameters such as redshift, CO(1–0) line width, or ΣSFR. We only find a tentative positive correlation between r 41 and the star-forming efficiency, but we are limited by our small sample size. Finally, we compare our results to predictions from the SHARK semi-analytical model, finding a good agreement between the molecular gas masses, depletion times, and gas fractions of our sources and their SHARK counterparts. Our results highlight the heterogeneous nature of the most massive SFGs at high redshift, and the importance of CO(1–0) observations to robustly constrain their total molecular gas content and interstellar medium properties.
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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 | 0.001 | 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 | 0.001 |
| 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".