Revised masses of dust and gas of SCUBA Local Universe Survey far-infrared bright galaxies based on a recent CO survey
Bibliographic record
Abstract
Recent CO measurements of an essentially complete subsample of galaxies from the SCUBA Local Universe Survey (SLUGS) are used to examine their implications for dust and gas masses in this sample. Estimates of dust masses are affected by a contribution to the SCUBA brightness measurements by CO(3–2) emission, and molecular gas masses by the use of a modified value of the CO-to-H2 conversion factor X. The average dust mass is reduced by 25–38 per cent, which has no bearing on earlier conclusions concerning the shape of the dust mass luminosity function derived from the SLUGS. The value of X found from the CO survey, when applied together with the reduction in dust masses, leads to lower estimates for the mean gas-to-dust mass ratios, where the gas includes both H2 and H i. For the CO sample, the mean global ratio is reduced from approximately 430 to about 320–360, but is further reduced to values near 50 when applied to the nuclear regions relevant to the CO observations. We discuss these results and suggest that the differences between the nuclear and outer regions may simply reflect differences in metallicity or the existence of considerable amounts of unobserved cold dust in the outer regions of these galaxies.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".