Resolving the Dust-to-Metals Ratio and CO-to-H<sub>2</sub> Conversion Factor in the Nearby Universe
Bibliographic record
Abstract
Abstract We investigate the relationship between the dust-to-metals ratio (D/M) and the local interstellar medium environment at ∼2 kpc resolution in five nearby galaxies: IC 342, M31, M33, M101, and NGC 628. A modified blackbody model with a broken power-law emissivity is used to model the dust emission from 100 to 500 μm observed by Herschel. We utilize the metallicity gradient derived from auroral line measurements in H i regions whenever possible. Both archival and new CO rotational line and H i 21 cm maps are adopted to calculate gas surface density, including new wide-field CO and H i maps for IC 342 from IRAM and the VLA, respectively. We experiment with several prescriptions of the CO-to-H2 conversion factor and compare the resulting D/M–metallicity and D/M–density correlations, both of which are expected to be nonnegative from depletion studies. The D/M is sensitive to the choice of the conversion factor. The conversion factor prescriptions based on metallicity only yield too much molecular gas in the center of IC 342 to obtain the expected correlations. Among the prescriptions tested, the one that yields the expected correlations depends on both metallicity and surface density. The 1σ range of the derived D/M spans 0.40–0.58. Compared to chemical evolution models, our measurements suggest that the dust growth timescale is much shorter than the dust destruction timescale. The measured D/M is consistent with the D/M in galaxy-integrated studies derived from infrared dust emission. Meanwhile, the measured D/M is systematically higher than the D/M derived from absorption, which likely indicates a systematic offset between the two methods.
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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 | 0.001 | 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".