A Map of the Outer Gas Disk of the Galaxy with Direct Distances from Young Stars
Bibliographic record
Abstract
Abstract For more than 50 yr, astronomers have mapped the neutral hydrogen gas in the Galaxy assuming kinematically derived distances. We employ the distances of nearby young stars, which trace the gas from which they formed, in longitude–latitude–velocity space to map this gas without using kinematic distances. We denote this new method “pattern matching.” Analysis of simulated spiral galaxies indicates that our pattern matching distances are 24% more accurate than kinematic distances for gas within 15 kpc of the Sun. The two methods provide similar agreement with parallaxes toward these masers, although the kinematic method shows a small systematic offset in distance that is not present in the pattern matching distances. Using parallaxes and velocities for masers, we show that this novel method, when matched with nearby Cepheids, performs well compared to kinematics. This analysis is restricted to sources that have a reasonably good match with a member of our Cepheid sample. The distances derived here, and the associated map, have broad utility—from improving our understanding of star formation and the dynamical structure of the Galaxy, to informing 3D dust maps.
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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 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".