PROBING THE IONIZATION STATES OF POLYCYCLIC AROMATIC HYDROCARBONS VIA THE 15–20<i>μ</i>m EMISSION BANDS
Bibliographic record
Abstract
We report new correlations between ratios of band intensities of the 15–20 μ m emission bands of polycyclic aromatic hydrocarbons (PAHs) in a sample of 57 sources observed with the Spitzer /Infrared Spectrograph. This sample includes Large Magellanic Cloud point sources from the SAGE-Spec survey, nearby galaxies from the Spitzer Infrared Nearby Galaxies Survey survey, two Galactic interstellar medium cirrus sources, and the spectral maps of the Galactic reflection nebulae NGC 2023 and NGC 7023. We find that the 16.4, 17.4, and 17.8 μ m band intensities are inter-correlated in all environments. In NGC 2023 and NGC 7023 these bands also correlate with the 11.0 and 12.7 μ m band intensities. The 15.8 μ m band correlates only with the 15–18 μ m plateau and the 11.2 μ m emission. We examine the spatial morphology of these bands and introduce radial cuts. We find that these bands can be spatially organized into three sets: the 12.7, 16.4, and 17.8 μ m bands; the 11.2, 15.8 μ m bands and the 15–18 μ m plateau; and the 11.0 and 17.4 μ m bands. We also find that the spatial distribution of the 12.7, 16.4, and 17.8 μ m bands can be reconstructed by averaging the spatial distributions of the cationic 11.0 μ m and neutral 11.2 μ m bands. We conclude that the 17.4 μ m band is dominated by cations, the 15.8 μ m band by neutral species, and the 12.7, 16.4, and 17.8 μ m bands by a combination of the two. These results highlight the importance of PAH ionization for spatially differentiating sub-populations by their 15–20 μ m emission variability.
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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) | 0.001 | 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".