Amidicity Change as a Significant Driving Force and Thermodynamic Selection Rule of Transamidation Reactions. A Synergy between Experiment and Theory
Bibliographic record
Abstract
Although essential in medicinal and industrial chemistry, transamidation reactions are still poorly understood mechanistically and in particular in terms of the extreme nature for their proceeding either very smoothly or not occurring at all. As yet, there exists no qualitative rule to predict the outcome of an amide interacting with an amine, with quantitative evaluations far from being established. In this paper we aim to clarify the thermodynamic selection rule and driving force of transamidation reactions based on amidicity value, measuring numerically the amide bond strength, toward providing a relatively simple protocol for practicing organic chemists to predict the outcome of an experiment. The change of amidicity over the course of a reaction made it possible to see that the process is favorable or unfavorable. This recently evaluated driving force of amidicity behaves analogously to the driving force of aromaticity in other organic reactions. This paper presents a successful comparison between empirical synthetic results and relevant computational characterizations, for a variety of transamidation reactions, all toward a synergy between experiments and theory. In this paper, we are re-examining experimentally and theoretically earlier experimental findings in relation to transamidation reactions and interpreting them from the aspect of amidicity change and stabilization enthalpies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".