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Truncated version of the reduced multireference coupled-cluster method with perturbation selection of higher than pair clusters

2000· article· en· W2023996671 on OpenAlexaff
Xiangzhu Li, Josef Paldus

Bibliographic record

VenueInternational Journal of Quantum Chemistry · 2000
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Chemical Physics Studies
Canadian institutionsUniversity of Waterloo
FundersRocky Mountain Research Station
KeywordsCoupled clusterWave functionChemistryPerturbation theory (quantum mechanics)Complete active spaceDissociation (chemistry)Selection (genetic algorithm)Configuration interactionCluster (spacecraft)Atomic physicsStatistical physicsComputational chemistryPhysicsQuantum mechanicsMoleculeDensity functional theoryPhysical chemistryBasis setComputer science

Abstract

fetched live from OpenAlex

A general implementation of a perturbatively truncated version of the reduced multireference (RMR) coupled-cluster method with singles and doubles (CCSD) [Peris, G. et al. J Chem Phys 1999, 110, 11708]—representing the MR-CISD-based version of the so-called externally corrected CCSD—is described and tested on several molecular systems involving the dissociation of a single bond of different character (HF and F2) as well as of a triple bond (N2). The possible pitfalls of a straightforward application of a perturbative selection scheme that is based on the first-order wave function coefficients are discussed, and different selection schemes are examined. It is shown that in order to obtain a stable and reliable scheme, it is necessary to exclude from the selection process all singles (and preferably all singles and doubles) relative to the leading Hartree–Fock reference configuration and retain them in the MR CISD wave function used as the external source of higher than pair connected clusters. The benefits of using perturbatively truncated RMR CCSD based on a large active space versus a nontruncated one, relying on a small model space, are also pointed out. © 2000 John Wiley & Sons, Inc. Int J Quant Chem 80: 743–756, 2000

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 score0.006
Threshold uncertainty score0.387

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 head0.009
GPT teacher head0.271
Teacher spread0.261 · 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

Citations46
Published2000
Admission routes1
Has abstractyes

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