Extinction and PAH intensity variations across the HII region IRAS 12063-6259
Bibliographic record
Abstract
The spatial variations in polycyclic aromatic hydrocarbon (PAH) band intensities are generally attributed to variations of the physical conditions in the environment hosting the emitting PAH molecules. However, in recent years, it has been suggested that such variations are caused mainly by extinction. To resolve this question, we have obtained near-infrared (NIR), mid-infrared (MIR) and radio observations of the compact HII region IRAS 12063-6259. We use these data to construct multiple independent extinction maps and to measure the main PAH feature intensities (6.2, 7.7, 8.6 and 11.2 µm). Three extinction maps are derived: the first using the NIR hydrogen lines and case B recombination theory; the second combining the NIR data, radio data and case B recombination; and the third making use of the Spitzer/IRS MIR observations to measure the 9.8 µm silicate absorption feature intensity using the Spoon method and PAHFIT. We conclude that different areas of IRAS 12063-6259 possess markedly different extinction properties, with some regions displaying both silicate absorption and corresponding NIR extinction, and other regions displaying NIR extinction and no corresponding silicate absorption. While such breakdowns of the relationship between the NIR extinction and the silicate absorption strength have been observed in molecular clouds, they have never been observed for HII regions. We then compare the PAH intensity variations in the Spitzer/IRS data after dereddening to those found in the original data. Generally it was found that the PAH band intensity variations persist even after dereddening, implying that extinction is not the main cause of the PAH band intensity variations.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".