Far-ultraviolet Dust Extinction and Molecular Hydrogen in the Diffuse Milky Way Interstellar Medium
Bibliographic record
Abstract
Abstract We aim to compare variations in the full-UV dust extinction curve (912–3000 Å), with the H i/H2/total H content along diffuse Milky Way sightlines, to investigate possible connections between ISM conditions and dust properties. We combine an existing sample of 75 UV extinction curves based on IUE and FUSE data, with atomic and molecular column densities measured through UV absorption. The H2 column density data are based on existing Lyman–Werner absorption band models from earlier work on the extinction curves. Literature values for the H i column density were compiled, and improved for 23 stars by fitting a Lyα profile to archived spectra. We discover a strong correlation between the H2 column and the far-UV extinction, and the underlying cause is a linear relationship between H2 and the strength of the far-UV rise feature. This extinction does not scale with H i, and the total H column scales best with A V instead. The carrier of the far-UV rise therefore coincides with molecular gas, and further connections are shown by comparing the UV extinction features to the molecular fraction. Variations in the gas-to-extinction ratio N ( H ) / A V correlate with the UV-to-optical extinction ratio, and we speculate this could be due to coagulation or shattering effects. Based on the H2 temperature, the strongest far-UV rise strengths are found to appear in colder and denser sightlines.
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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 | 0.001 |
| 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".