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Record W2599825791 · doi:10.1063/1.4977732

Theoretical volume profiles for conformational changes: Application to internal rotation of benzene ring in 1,12-dimethoxy-[12]-paracyclophane

2017· article· en· W2599825791 on OpenAlexafffund
Heather Wiebe, Miranda Louwerse, Noham Weinberg

Bibliographic record

VenueThe Journal of Chemical Physics · 2017
Typearticle
Languageen
FieldChemistry
TopicSynthesis and Properties of Aromatic Compounds
Canadian institutionsUniversity of the Fraser ValleySimon Fraser University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsRing (chemistry)BenzeneTransition state theoryChemistryWork (physics)Transition stateKinetic energyGibbs free energyVolume (thermodynamics)ThermodynamicsMethyleneKineticsReaction coordinateActivation energyRotation (mathematics)Computational chemistryChemical physicsStatistical physicsPhysical chemistryReaction rate constantPhysicsComputer scienceOrganic chemistryCatalysisClassical mechanics

Abstract

fetched live from OpenAlex

Identification of the transition state is an important step in the study of reaction kinetics and mechanisms. However, for non-rigid chemical systems where multiple viable reaction pathways may exist, enumeration of all possible transition states quickly becomes computationally expensive, if at all feasible. As an alternative approach, we recently proposed a methodology where the volumetric properties of a flexible reaction system are used to locate its transition state ensemble through a comparison of its theoretically determined volume profile and experimental activation volumes derived from high pressure kinetic data. In this work, we apply this method to internal rotation of the benzene ring in 1,12-dimethoxy-[12]-paracyclophane. For this system, the transition state ensemble was found to be the state with the lowest volume, where the benzene ring and the flexible methylene tether are coplanar. This result was verified by comparison with a Gibbs free energy profile obtained via umbrella sampling.

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)0.000
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 score0.053
Threshold uncertainty score0.308

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.020
GPT teacher head0.274
Teacher spread0.254 · 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

Citations5
Published2017
Admission routes2
Has abstractyes

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