Rate constants for formation of bisulfite addition compounds: an examination in terms of No Barrier Theory
Bibliographic record
Abstract
We report a study of the rates of sulfite addition to carbonyl compounds. This reaction is useful in separating compounds (aldehydes react more extensively than ketones, thus becoming water soluble) because the reaction is readily reversible. Although the reaction is mainly by addition of sulfite dianion, the equilibrium is much more favorable for the addition of bisulfite to give a monoanionic adduct. It is also of interest because bisulfite addition is very favorable; thus, we are dealing with a very strong nucleophile. This work demonstrates that No Barrier Theory can calculate rates for good nucleophiles (cyanide and now sulfite) as well as poor nucleophiles such as water. It has been necessary to develop good ways to handle the anionic tetrahedral adducts (in the case of sulfite as nucleophile, dianionic), which tend to break down in the gas phase unless explicitly solvated, and modified procedures for crowded transition states to allow for some relief of steric congestion while maintaining the essential definition of the distorted species resulting from bond formation without geometry change.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".