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Record W1982539988 · doi:10.1139/v08-052

Localized-orbital locator (LOL) profiles of chemical bonding

2008· article· en· W1982539988 on OpenAlexvenueno aff
Heiko Jacobsen

Bibliographic record

VenueCanadian Journal of Chemistry · 2008
Typearticle
Languageen
FieldChemistry
TopicCrystallography and molecular interactions
Canadian institutionsnot available
Fundersnot available
KeywordsHypervalent moleculeChemical bondChemistryThree-center two-electron bondElectron pairCore electronChemical physicsElectron localization functionMoleculeElectron densityValence electronElectronDensity functional theoryKinetic energyComputational chemistryAtomic orbitalCovalent bondMolecular physicsMolecular orbitalValence bond theoryPhysicsPhysical chemistryQuantum mechanicsOrganic chemistry

Abstract

fetched live from OpenAlex

We examine a recently introduced descriptor of chemical bonding, the localized-orbital locator (LOL), which is based on the kinetic-energy density (τ). Examples are presented for prototypical chemical bonds, such as single, double, and triple bonds, for bonding in transition metal complexes, for three-center two-electron bonds, as well as for hypervalent molecules. The topology of LOL is analyzed in terms of (3,–3) attractors (Γ). The influence of core electrons for chemical bonding is investigated, and a LOL-VSEPR (valence shell electron pair repulstion) relationship is established. Further, we compare LOL to the related electron localization function (ELF).Key words: chemical bonding, kinetic-energy density, localized-electron locator, VSEPR theory.

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)0.001
metaresearch head score (Gemma)0.002
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: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.000

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 head0.214
Teacher spread0.204 · 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
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

Citations443
Published2008
Admission routes1
Has abstractyes

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