PAHs and star formation in the H ii regions of nearby galaxies M83 and M33
Bibliographic record
Abstract
We present mid-infrared (MIR) spectra of |$\rm{H\,{{\small II}}}$| regions within star-forming galaxies M83 and M33. Their emission features are compared with Galactic and extragalactic |$\rm{H\,{{\small II}}}$| regions, |$\rm{H\,{{\small II}}}$|-type galaxies, starburst galaxies, and Seyfert/LINER type galaxies. Our main results are as follows: (i) the M33 and M83 H ii regions lie in between Seyfert/LINER galaxies and |$\rm{H\,{{\small II}}}$|-type galaxies in the 7.7/11.3–6.2/11.3 plane, while the different sub-samples exhibit different 7.7/6.2 ratios; (ii) Using the NASA Ames PAH IR Spectroscopic database, we demonstrate that the 6.2/7.7 ratio does not effectively track PAH size, but the 11.3/3.3 PAH ratio does; (iii) variations on the 17 μm PAH band depends on object type; however, there is no dependence on metallicity for both extragalactic |$\rm{H\,{{\small II}}}$| regions and galaxies; (iv) the PAH/VSG intensity ratio decreases with the hardness of the radiation field and galactocentric radius (Rg), yet the ionization alone cannot account for the variation seen in all of our sources; (v) the relative strength of PAH features does not change significantly with increasing radiation hardness, as measured through the [|$\rm{Ne\,{{\small III}}}$|]/[|$\rm{Ne\,{{\small II}}}$|] ratio and the ionization index; (vi) We present PAH SFR calibrations based on the tight correlation between the 6.2, 7.7, and 11.3 μm PAH luminosities with the 24 μm luminosity and the combination of the 24 μm and H α luminosity; (vii) Based on the total luminosity from PAH and FIR emission, we argue that extragalactic |$\rm{H\,{{\small II}}}$| regions are more suitable templates in modelling and interpreting the large-scale properties of galaxies compared to Galactic |$\rm{H\,{{\small II}}}$| 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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.001 | 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".