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Record W4408038891 · doi:10.1080/00268976.2025.2466666

Using an uncontracted inter-molecular basis to assess the convergence of contracted inter-molecular bases when computing the spectrum of H <sub>2</sub> O-CO

2025· article· en· W4408038891 on OpenAlexafffund
Xiaogang Wang, Tucker Carrington

Bibliographic record

VenueMolecular Physics · 2025
Typearticle
Languageen
FieldChemistry
TopicSpectroscopy and Laser Applications
Canadian institutionsQueen's University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsConvergence (economics)ChemistryBasis (linear algebra)Molecular dynamicsSpectrum (functional analysis)Computational chemistryComputer sciencePhysicsMathematicsQuantum mechanicsGeometry

Abstract

fetched live from OpenAlex

We report energy levels of H2O-CO computed with a large product contracted (PC) basis. Intra-molecular levels are obtained using a large basis of products of contracted intra-molecular functions and contracted inter-molecular functions. To determine the size of the contracted inter-molecular basis required to achieve convergence, we compute inter-molecular levels without contracting the inter-molecular basis. We call this a |v,L⟩ basis. We find that a large contracted inter-molecular basis is necessary. Previous calculations with a smaller inter-molecular basis have convergence errors similar to those caused by using the rigid-monomer approximation. For example, the largest relative splitting error is 37%. Owing to the size of the inter-molecular basis, a quadrature-point intermediate matrix F, rather than a DVR-point intermediate matrix F, and MPI parallelisation are important for reducing the calculation time.

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)0.004
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: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.021
GPT teacher head0.301
Teacher spread0.280 · 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

Citations4
Published2025
Admission routes2
Has abstractyes

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