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Record W2117019956 · doi:10.1002/qua.10538

Numerical methods for multicenter integrals for numerically defined basis functions applied in molecular calculations

2003· article· en· W2117019956 on OpenAlexafffund
James D. Talman

Bibliographic record

VenueInternational Journal of Quantum Chemistry · 2003
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Chemical Physics Studies
Canadian institutionsWestern University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSlater integralsOrder of integration (calculus)Basis (linear algebra)Basis functionConvergence (economics)Coordinate spacePhysicsSpace (punctuation)Statistical physicsMathematicsQuantum mechanicsMathematical analysisComputer scienceGeometry

Abstract

fetched live from OpenAlex

Abstract An alternative approach to using functions defined analytically as basis functions for molecular orbital calculations is to use functions defined numerically on some mesh. It is then necessary to evaluate various integrals involving products of such functions that are centered at different points in space, usually the nuclei. This article discusses in detail the problem of evaluating overlap and kinetic energy integrals, nuclear attraction three‐center integrals, and electron–electron repulsion four‐center integrals for such functions. The problem of evaluating these functions in translated coordinate systems, which arises in density functional theory applications, and the associated convergence problems are also discussed. © 2003 Wiley Periodicals, Inc. Int J Quantum Chem, 2003

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)0.006
metaresearch head score (Gemma)0.017
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: Methods · Consensus signal: Methods
Teacher disagreement score0.006
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.017
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0010.002
Scholarly communication0.0020.002
Open science0.0020.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0050.002

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 head0.350
Teacher spread0.332 · 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

Citations28
Published2003
Admission routes2
Has abstractyes

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