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Record W4393119741 · doi:10.1002/qua.27364

Towards universal substituent constants: Parameterizing bond critical point properties with electronegativity descriptors

2024· article· en· W4393119741 on OpenAlexafffund
Kevin M. Lefrancois‐Gagnon, Robert C. Mawhinney

Bibliographic record

VenueInternational Journal of Quantum Chemistry · 2024
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Chemical Physics Studies
Canadian institutionsLakehead University
FundersQueen Elizabeth ScholarsAlliance de recherche numérique du CanadaLakehead University
KeywordsElectronegativitySubstituentComputational chemistryPoint (geometry)ChemistryThermodynamicsPhysicsMathematicsStereochemistryOrganic chemistryGeometry

Abstract

fetched live from OpenAlex

Abstract The properties of substituents have long been quantified by their effect elsewhere in a molecule. Ideally, intrinsic properties detailing the true properties of a substituent would be used. These properties are ideally transferable between molecules, to be robust and applied in different situations. Through a study on the bond critical point (BCP) properties of 117 substituents and 17 substrates we find that BCP properties from the quantum theory of atoms in molecules are not transferable between different bonded atoms. However, a substituent's changing electronegativity between substrates help quantify the observed variation. The relationship between changing electronegativities and critical point properties enables development of a relationship to predict critical point properties between a substituent and a new substrate, using only the electronegativity of a substituent attached to hydrogen, and the critical point property between the substituent and H.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.002
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
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 head0.017
GPT teacher head0.271
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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreMethods

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

Citations1
Published2024
Admission routes2
Has abstractyes

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