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Record W1978738413 · doi:10.1063/1.1650327

Performance of the general-model-space state-universal coupled-cluster method

2004· article· en· W1978738413 on OpenAlexafffund
Xiangzhu Li, Josef Paldus

Bibliographic record

VenueThe Journal of Chemical Physics · 2004
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Chemical Physics Studies
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsExcited stateCoupled clusterExcitationAtomic physicsSpace (punctuation)Potential energyPhysicsGround stateBasis setSeries (stratigraphy)Quantum mechanicsMoleculeComputer science

Abstract

fetched live from OpenAlex

The capabilities of the recently developed multireference, general-model-space (GMS), state-universal (SU) coupled-cluster (CC) method have been extended in order to enable the handling of any excited state that represents a single (S) or a double (D) excitation relative to the ground state. A series of calculations concerning the ground and excited states of the CH(+), HF, F(2), H(2)O, NH(2), and CH(2) molecules were carried out so as to assess the performance of the GMS SU CCSD method. For diatomics we have computed the entire potential energy curves, while for triatomics we have focused on vertical excitation energies. We demonstrate how a systematic enlargement of the model space enables a consideration of a larger and larger number of excited states. A comparison of the CC and full configuration interaction or large-scale CI results enables an assessment of the accuracy and reliability of the GMS SU CCSD method within a given basis set. In all cases very good results have been obtained, including highly excited states and those having a doubly-excited character.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.016
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.260
Teacher spread0.250 · 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 designSimulation or modeling
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

Citations71
Published2004
Admission routes2
Has abstractyes

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