The opacity of spiral galaxy disks: IX. Dust and gas surface densities
Bibliographic record
Abstract
Abstract Our aim is to explore the relation between gas, atomic and molecular, and dust in spiral galaxies. Gas surface densities are from atomic hydrogen and CO line emission maps. To estimate the dust content, we use the disk opacity as inferred from the number of distant galaxies identified in twelve HST/WFPC2 fields of ten nearby spiral galaxies. The observed number of distant galaxies is calibrated for source confusion and crowding with artificial galaxy counts and here we verify our results with sub‐mm surface brightnesses from archival Herschel ‐SPIRE data. We find that the opacity of the spiral disk does not correlate well with the surface density of atomic (H I) or molecular hydrogen (H2) alone implying that dust is not only associated with the molecular clouds but also the diffuse atomic disk in these galaxies. Our result is a typical dust‐to‐gas ratio of 0.04, with some evidence that this ratio declines with galactocentric radius, consistent with recent Herschel results. We discuss the possible causes of this high dust‐to‐gas ratio; an over‐estimate of the dust surface‐density, an under‐estimate of the molecular hydrogen density from CO maps or a combination of both. We note that while our value of the mean dust‐to‐gas ratio is high, it is consistent with the metallicity at the measured radii if one assumes the Pilyugin & Thuan (2005) calibration of gas metallicity. (© 2013 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".