Spectral variations among different scenarios of PAH processing or formation
Bibliographic record
Abstract
ABSTRACT We examine the variations in the spectral characteristics and intensities of polycyclic aromatic hydrocarbons (PAHs) in two different scenarios of PAH processing (or formation): (1) small PAHs are being destroyed (or equivalently large PAHs are being formed, referred to as SPR, i.e. small PAHs removed), and (2) large PAHs are being destroyed (or equivalently small PAHs are being formed, referred to as LPR, i.e. large PAHs removed). PAH emission was measured considering both the presence and absence of plateau components. The variation in the PAH band intensities as a function of the average number of carbon atoms 〈NC〉 has the highest dynamic range in the SPR case, suggesting that smaller PAHs have higher impact on the PAH band strengths. The plateaus show overall declining emission with 〈NC〉, and their higher dynamic range in the SPR case also suggests that smaller PAHs are mainly contributing to the plateau emission. The 7.7/(11.0 + 11.2) $\mu$m PAH band ratio presents the least amount of variance with the lowest dynamic range, rendering this ratio as the better choice for tracing PAH charge. The 3.3/(11.2 + 11.0) $\mu$m PAH band ratio is the only ratio that has both a monotonic variance and fully separated values among the SPR and LPR scenarios, highlighting its efficiency as PAH size tracer but also allowing the characterization of the dominant scenario of processing or formation in a given region or source. We present new PAH charge–size diagnostic diagrams, which can provide insights into the average, maximum, or minimum NC within astrophysical sources.
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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 | 0.000 |
| 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 | 0.000 |
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".