A survey of the cold molecular gas in gravitationally lensed star-forming galaxies at<i>z</i>> 2
Bibliographic record
Abstract
Using the Australia Telescope Compact Array, we conducted a survey of CO J = 1 − 0 and J = 2 − 1 line emission towards strongly lensed high-redshift dusty star-forming galaxies (DSFGs) previously discovered with the South Pole Telescope (SPT). Our sample comprises 17 sources that had CO-based spectroscopic redshifts obtained with the Atacama Large Millimeter/submillimeter Array and the Atacama Pathfinder Experiment. We detect all sources with known redshifts in either CO J = 1 − 0 or J = 2 − 1. 12 sources are detected in the 7-mm continuum. The derived CO luminosities imply gas masses in the range (0.5–11) × 1010 M⊙ and gas depletion time-scales tdep < 200 Myr, using a CO to gas mass conversion factor αCO = 0.8 M⊙ (K km s−1 pc2)−1. Combining the CO luminosities and dust masses, along with a fixed gas-to-dust ratio, we derive αCO factors in the range 0.4–1.8 M⊙ (K km s−1 pc2)−1, similar to what is found in other starbursting systems. We find small scatter in αCO values within the sample, even though inherent variations in the spatial distribution of dust and gas in individual cases could bias the dust-based αCO estimates. We find that lensing magnification factors based on the CO linewidth to luminosity relation (μCO) are highly unreliable, but particularly when μ < 5. Finally, comparison of the gas and dynamical masses suggest that the average molecular gas fraction stays relatively constant at z = 2–5 in the SPT DSFG sample.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".