Can a local mode picture account for vibration–torsion coupling? <i>Ab initio</i> test based on torsional variation of methyl stretching and bending frequencies in methanol
Bibliographic record
Abstract
The torsional dependence of the CH3 stretching and bending modes of methanol has been explored in terms of a local mode internal coordinate picture [X. Wang and D. S. Perry, J. Chem. Phys. 109, 10795 (1998)]. First, the torsional variations of the small-amplitude vibrational frequencies along the mass weighted intrinsic reaction coordinate from the top to the bottom of the torsional potential barrier were calculated by means of ab initio frequency projection utilizing GAUSSIAN 98. The resulting curves for the three C–H stretch ab initio frequencies as functions of the torsional angle cannot be reproduced by the original 3×3 local mode model incorporating stretch–torsion and stretch–stretch couplings at lowest-order only, but are well-fitted if the model is extended to include higher-order coupling terms. For the CH-bending modes, with internal coordinates chosen to give a high degree of localization, bend–torsion and bend–bend coupling parameters were determined from the ab initio projected frequencies, and were then used to predict torsional tunneling splittings. Just as observed for the C–H stretch modes, the two higher-frequency asymmetric CH-bend modes are predicted to have inverted tunneling splittings with reduced amplitudes, while the splitting pattern for the lower frequency symmetric-bend mode is predicted to be normal.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".