All We Are Is Dust in the WIM: Constraints on Dust Properties in the Milky Way’s Warm Ionized Medium
Bibliographic record
Abstract
Abstract We present a comparison of the presence and properties of dust in two distinct phases of the Milky Way’s interstellar medium: the warm neutral medium (WNM) and the warm ionized medium (WIM). Using distant pulsars at high Galactic latitudes and vertical distance (∣b∣ > 40°, D sin ∣ b ∣ > 2 kpc ) as probes, we measure their dispersion measures and the neutral hydrogen component of the warm neutral medium (WNMH I) using H i column density. Together with dust intensity along these same sightlines, we separate the respective dust contributions of each ISM phase in order to determine whether the ionized component contributes to the dust signal. We measure the temperature (T), spectral index (β), and dust opacity (τ/N H) in both phases. We find T ( WNM H I ) = 20 − 2 + 3 K, β (WNMH I) = 1.5 ± 0.4, and τ 353/N H (WNMH I) = (1.0 ± 0.1) × 10−26 cm2. Assuming that the temperature and spectral index are the same in both the WNMH I and WIM, and given our simple model that widely separated lines of sight can be fit together, we find evidence that there is a dust signal associated with the ionized gas and τ 353 / N H ( WIM ) = ( 0.3 ± 0.3 ) × 10 − 26 , which is about 3 times smaller than τ 353/N H (WNMH I). We are 80% confident that τ 353 / N H ( WIM ) is at least 2 times smaller than τ 353/N H (WNMH I).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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".