MétaCan
Menu
Back to cohort
Record W2009936404 · doi:10.1063/1.1645780

The impact of the multipolar distribution on chiral discrimination in racemates

2004· article· en· W2009936404 on OpenAlexafffund
Irina Paci, N. M. Cann

Bibliographic record

VenueThe Journal of Chemical Physics · 2004
Typearticle
Languageen
FieldChemistry
TopicAnalytical Chemistry and Chromatography
Canadian institutionsQueen's University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsQuadrupoleDipoleChemistryEnantiomerMoment (physics)Intermolecular forcePerpendicularDistribution (mathematics)Orientation (vector space)PhysicsAtomic physicsStereochemistryClassical mechanicsMoleculeOrganic chemistryGeometry

Abstract

fetched live from OpenAlex

This article explores the impact of the multipolar distribution on chiral discrimination in a series of racemic fluids. Discrimination is measured via the difference between the like-like (LL) and the like-unlike (LU) radial distributions in the liquid. We have found previously that the magnitude and orientation of the molecular dipole have a decisive impact on the short-ranged enantiomeric imbalance in racemates. Although quadrupolar and octupolar interactions decrease more rapidly with intermolecular separation, they can be significant at small separations, where enantiomeric imbalances occur. We have carefully selected a number of models in which we isolate the effects of the molecular quadrupole and octupole. We find that discrimination can be greatly enhanced by changes in the quadrupole moments. However, for octupole moments, changes in discrimination are small and some octupoles inhibit discrimination. We identify the quadrupole moment closest to the plane perpendicular to the direction of the molecular dipole as the moment that has the greatest favorable effect on chiral discrimination in racemates. In racemates where this moment is large, we have found differences of up to 40% between the LL and the LU radial distributions.

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)0.000
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 score0.033
Threshold uncertainty score0.212

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0000.000
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 head0.008
GPT teacher head0.257
Teacher spread0.249 · 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

Citations4
Published2004
Admission routes2
Has abstractyes

Explore more

Same venueThe Journal of Chemical PhysicsSame topicAnalytical Chemistry and ChromatographyFrench-language works237,207