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Record W1964396782 · doi:10.1063/1.1323260

Reduced multireference coupled cluster method: Ro-vibrational spectra of N2

2000· article· en· W1964396782 on OpenAlexaff
Xiangzhu Li, Josef Paldus

Bibliographic record

VenueThe Journal of Chemical Physics · 2000
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Chemical Physics Studies
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsMultireference configuration interactionExcited stateCoupled clusterAtomic physicsPotential energyBasis setChemistryValence (chemistry)Raman spectroscopyConfiguration interactionMoleculePhysicsComputational chemistryQuantum mechanicsDensity functional theory

Abstract

fetched live from OpenAlex

The reduced multireference (RMR) coupled cluster method with singles and doubles (CCSD), relying on four- and eight-dimensional reference spaces, is employed to generate the potential energy curve for the nitrogen molecule, using both the correlation-consistent polarized valence-triple-zeta (cc-pVTZ) and atomic natural orbital basis sets. The resulting potentials are then used to compute the ro-vibrational term values, which are compared with the available experimentally determined values. Moreover, a direct comparison with the measured spectral line frequencies, for both the fundamental rotational Raman band and the vibrationally excited Q branches, is also carried out. Comparisons with the single reference CCSD, as well as with the corresponding multireference configuration interaction results that serve as the external source for RMR CCSD, are also made. An excellent performance of RMR CCSD, and its systematic improvement with the increasing dimension of the reference space employed, is demonstrated for the cc-pVTZ basis set. The fundamental Raman band frequencies are computed with an error of less than 1 cm−1, while for the vibrationally excited bands a systematic deviation of about 7 cm−1 is found.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.287
Teacher spread0.270 · 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

Citations94
Published2000
Admission routes1
Has abstractyes

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