Bibliographic record
Abstract
Context. Photodissociation regions (PDRs) exhibit strong emission bands between 3–20 μm known as the aromatic infrared bands (AIBs), and they originate from small carbonaceous species such as polycyclic aromatic hydrocarbons (PAHs) excited by UV radiation. The AIB spectra observed in Galactic PDRs are considered a local analog for those seen in extragalactic star-forming regions. Recently, the PDRs4All JWST program observed the Orion Bar PDR, revealing the subcomponents and profile variations of the AIBs in very high detail. Aims. We present the Python version of PAHFIT, a spectral decomposition tool that separates the contributions by AIB subcomponents, thermal dust emission, gas lines, stellar light, and dust extinction. We aim to provide a configuration that enables highly detailed decompositions of JWST spectra of PDRs (3.1–26 μm) and to test if the same configuration is suitable to characterize AIB emission in extragalactic star forming regions. Methods. We determined the central wavelength and FWHM of the AIB subcomponents by fitting selected segments of the Orion Bar spectra and compiled them into a “PDR pack” for PAHFIT. We tested the PDR pack by applying PAHFIT to the full 3.1–26 μm PDRs4All templates. We applied PAHFIT with this PDR pack and the default continuum model to seven spectra extracted from the central star forming ring of the galaxy NGC7469. Results. We introduce an alternate dust continuum model to fit the Orion Bar spectra, as the default PAHFIT continuum model mismatches the intensity at 15–26 μm. Using the PDR pack and the alternate continuum model, PAHFIT reproduces the Orion Bar template spectra with residuals of a few percent. A similar performance is achieved when applying the PDR pack to the NGC7469 spectra. We provide PAHFIT-based diagnostics that trace the profile variations of the 3.3, 3.4, 5.7, 6.2, and 7.7 μm AIBs and thus the photochemical evolution of the AIB carriers. The 5.7 μm AIB emission originates from at least two subpopulations, one more prominent in highly irradiated environments and one preferring more shielded environments. Smaller PAHs as well as very small grains or PAH clusters both thrive in the more shielded environments of the molecular zone in the Orion Bar. Based on these new diagnostics, we show and quantify the strong similarity of the AIB profiles observed in NGC7469 to the Orion Bar template spectra.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.095 | 0.096 |
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".