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Record W4386988767 · doi:10.1002/qua.27246

Accuracy of expectation values of one‐electron operators obtained from Hartree–Fock wavefunctions expanded using Lambda functions

2023· article· en· W4386988767 on OpenAlexaff
Yasuyo Hatano, Shigeyoshi Yamamoto, Hiroshi Tatewaki

Bibliographic record

VenueInternational Journal of Quantum Chemistry · 2023
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Chemical Physics Studies
Canadian institutionsArtificial Intelligence in Medicine (Canada)
Fundersnot available
KeywordsWave functionCusp (singularity)ElectronHomogeneous spaceLambdaAtomic physicsLimit (mathematics)Hartree–Fock methodPhysicsQuantum mechanicsValue (mathematics)Mathematical physicsChemistryMathematicsMathematical analysisStatisticsGeometry

Abstract

fetched live from OpenAlex

Abstract The accuracy of the expectation values () of one‐electron operators is examined using Hartree–Fock wavefunctions expanded using functions. In this expansion, 150 terms, then 149, 148, and 147 terms are used for the s‐, p‐, d‐, and f‐symmetries, respectively. The systems investigated are He–Ne and the Group 18 atoms of Ar–Og. The one‐electron properties investigated are the cusp condition (CC), the electron density at the nucleus (), and (). Convergence of is examined by increasing the number of expansion terms () up to the given limit (150). The number of significant figures (SF) of is counted by comparing the calculated value at =150 () with the extrapolated value . For He, the SF of CC is found to be 26. For the atoms under consideration, the SF of CC is approximately half that of the total energy (TE). The SFs of expectation values of the other properties are also smaller than for the TE.

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 score0.032
Threshold uncertainty score0.570

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 head0.028
GPT teacher head0.315
Teacher spread0.287 · 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

Citations2
Published2023
Admission routes1
Has abstractyes

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