LINE EMISSION FROM RADIATION-PRESSURIZED H II REGIONS. I. INTERNAL STRUCTURE AND LINE RATIOS
Bibliographic record
Abstract
The emission line ratios [O iii ] λ5007/Hβ and [N ii ] λ6584/Hα have been adopted as an empirical way to distinguish between the fundamentally different mechanisms of ionization in emission-line galaxies. However, detailed interpretation of these diagnostics requires calculations of the internal structure of the emitting H ii regions, and these calculations depend on the assumptions one makes about the relative importance of radiation pressure and stellar winds. In this paper, we construct a grid of quasi-static H ii region models to explore how choices about these parameters alter H ii regions' emission line ratios. We find that when radiation pressure is included in our models, H ii regions reach a saturation point beyond which further increase in the luminosity of the driving stars does not produce any further increase in effective ionization parameter, and thus does not yield any further alteration in an H ii region's line ratio. We also show that if stellar winds are assumed to be strong, the maximum possible ionization parameter is quite low. As a result of this effect, it is inconsistent to simultaneously assume that H ii regions are wind-blown bubbles and that they have high ionization parameters; some popular H ii region models suffer from this inconsistency. Our work in this paper provides a foundation for a companion paper in which we embed the model grids we compute here within a population synthesis code that enables us to compute the integrated line emission from galactic populations of H ii regions.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".