A VLA Census of the Galactic H II Region Population
Bibliographic record
Abstract
Abstract The Milky Way contains thousands of H ii region candidates identified by their characteristic mid-infrared morphology, but lacking detections of ionized gas tracers such as radio continuum or radio recombination line emission. These targets thus remain unconfirmed as H ii regions. With only ∼2500 confirmed H ii regions in the Milky Way, Galactic surveys are deficient by several thousand nebulae when compared to external galaxies with similar star formation rates. Using sensitive 9 GHz radio continuum observations with the Karl G. Jansky Very Large Array, we explore a sample of H ii region candidates in order to set observational limits on the actual total population of Galactic H ii regions. We target all infrared–identified “radio-quiet” sources from the Wide-field Infrared Survey Explorer Catalog of Galactic H ii regions between 245° ≥ ℓ ≥ 90° with infrared diameters less than 80′′. We detect radio continuum emission from 50% of the targeted H ii region candidates, providing strong evidence that most of the radio-quiet candidates are bona fide H ii regions. We measure the peak and integrated radio flux densities and compare the inferred Lyman continuum fluxes using models of OB stars. We conclude that stars of approximately spectral type B2 and earlier are able to create H ii regions with similar infrared and radio continuum morphologies as the more luminous H ii regions created by O stars. From our 50% detection rate of “radio-quiet” sources, we set a lower limit of ∼7000 for the H ii region population of the Galaxy. Thus the vast majority of the Milky Way’s H ii regions remain to be discovered.
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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 | 0.002 | 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) | 0.002 | 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".