A QUANTUM BAND MODEL OF THE ν<sub>3</sub>FUNDAMENTAL OF METHANOL (CH<sub>3</sub>OH) AND ITS APPLICATION TO FLUORESCENCE SPECTRA OF COMETS
Bibliographic record
Abstract
Methanol (CH 3 OH) radiates efficiently at infrared wavelengths, dominating the C–H stretching region in comets, yet inadequate quantum-mechanical models have imposed limits on the practical use of its emission spectra. Accordingly, we constructed a new line-by-line model for the ν 3 fundamental band of methanol at 2844 cm −1 (3.52 μm) and applied it to interpret cometary fluorescence spectra. The new model permits accurate synthesis of line-by-line spectra for a wide range of rotational temperatures, ranging from 10 K to more than 400 K. We validated the model by comparing simulations of CH 3 OH fluorescent emission with measured spectra of three comets (C/2001 A2 LINEAR, C/2004 Q2 Machholz and 8P/Tuttle) acquired with high-resolution infrared spectrometers at high-altitude sites. The new model accurately describes the complex emission spectrum of the ν 3 band, providing distinct rotational temperatures and production rates at greatly improved confidence levels compared with results derived from earlier fluorescence models. The new model reconciles production rates measured at infrared and radio wavelengths in C/2001 A2 (LINEAR). Methanol can now be quantified with unprecedented precision and accuracy in astrophysical sources through high-dispersion spectroscopy at infrared wavelengths.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".