The NASA Ames PAH IR Spectroscopic Database and the far-IR
Bibliographic record
Abstract
Polycyclic Aromatic Hydrocarbons (PAHs) are widespread across the Universe and influence many stages of the Galactic lifecycle.The presence of PAHs has been well established and the rich mid-IR PAH spectrum is now commonly used as a probe into (inter)stellar environments.The NASA Ames PAH IR Spectroscopic Database has been key to test and refine the "PAH hypothesis".This database is a large coherent set (>600 spectra) of laboratory measured and DFT computed infrared spectra of PAHs from C10H8 to C130H28 and has been made available on the web at (http://www.astrochem.org/pahdb).With a new spectral window opening up; the far-IR, the study of PAH far-IR spectra and the quest for identifying a unique member of the interstellar PAH family has begun.To guide this research, the far-IR (>20 μm) spectra of different sets of PAHs are investigated using the NASA Ames PAH IR Spectroscopic Database.These sets explore the influence of size, shape, charge and composition on the far-IR PAH spectrum.The far-IR is also the domain of the so-called "drumhead" modes and other molecular vibrations involving low order bending vibrations of the carbon skeleton as a whole.As with drums, these are molecule and shape specific and promise to be a key diagnostic for specific PAHs.Here, the sensitivity of these "drumhead" modes to size and shape is assessed by comparing the frequencies of the lowest drumhead modes of a family of circular shaped (the coronene "family") and rhombus shaped (the pyrene "family") PAH molecules.From this study, some consequences for an observing strategy are drawn.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 0.013 |
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".