Separation of quantum and classical behavior in proton transfer reactions: Implications from studies of secondary kinetic isotope effects
Bibliographic record
Abstract
Abstract In this article the separability of the nuclear degrees of freedom system into mixed quantum and classical components is examined by looking at secondary kinetic isotope effects in a model proton transfer reaction. To explore this issue, the nature of secondary kinetic isotope effects is investigated by means of molecular mechanics and ab initio simulations of a model system in which intramolecular proton transfer occurs in a region whose chemical topology is similar to that of malonaldehyde. Isotope effects are calculated using importance sampling Monte Carlo techniques designed to improve the statistical efficiency of ab initio simulations within the framework of quantum centroid transition state theory. The ab initio results for kinetic isotope effects are contrasted with those obtained using two molecular mechanics potential energy functions. It is demonstrated that the calculated isotope effects are extremely sensitive to subtle features of the potential energy surface, which suggests that information from ab initio structure and energy calculations about configurations along the reaction path must be utilized in the construction of classical potentials to obtain accurate secondary kinetic isotope effect predictions. It is also demonstrated that quantum nuclear degrees of freedom of all secondary atoms that move significantly as a chemical reaction proceeds should be treated explicitly, as even secondary heavy‐atom tunneling effects could be significant. © 2002 Wiley Periodicals, Inc. Int J Quantum Chem, 2003
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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".