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Record W1893806853 · doi:10.1139/cjc-2014-0270

Rate constants for formation of bisulfite addition compounds: an examination in terms of No Barrier Theory

2014· article· en· W1893806853 on OpenAlexaffvenue
J. Peter Guthrie, Yinyin Wu, Alexander R. Bannister, Sriyawathie Peiris, Igor Povar, Elizabeth Wilson, Qiang Wang

Bibliographic record

VenueCanadian Journal of Chemistry · 2014
Typearticle
Languageen
FieldChemistry
TopicChemical Reaction Mechanisms
Canadian institutionsWestern University
Fundersnot available
KeywordsBisulfiteChemistryNucleophileSulfiteAdductSteric effectsNucleophilic additionCyanideSodium bisulfiteComputational chemistryOrganic chemistryPhotochemistryCatalysis

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.704

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.010
GPT teacher head0.218
Teacher spread0.209 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations3
Published2014
Admission routes2
Has abstractyes

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