MétaCan
Menu
Back to cohort
Record W2312708590 · doi:10.1021/ct300248n

Parameterized Bases for Calculating Vibrational Spectra Directly from ab Initio Data Using Rectangular Collocation

2012· article· en· W2312708590 on OpenAlexaff
Matthew Chan, Sergei Manzhos, Tucker Carrington, Koichi Yamashita

Bibliographic record

VenueJournal of Chemical Theory and Computation · 2012
Typearticle
Languageen
FieldPhysics and Astronomy
TopicSpectroscopy and Quantum Chemical Studies
Canadian institutionsQueen's UniversityMcMaster University
Fundersnot available
KeywordsAnharmonicityHermite polynomialsAb initioGaussianBasis setBasis functionPotential energyHarmonicParameterized complexityBasis (linear algebra)PhysicsParametrization (atmospheric modeling)Computational chemistryStatistical physicsChemistryMathematicsQuantum mechanicsAlgorithmGeometryMolecule

Abstract

fetched live from OpenAlex

We compared different parametrized bases for computing anharmonic vibrational spectra using a new version of the rectangular collocation-optimization method of Manzhos and Carrington (Can. J. Chem. 2009, 87, 864; Chem. Phys. Lett. 2011, 511, 434). The method enables one to compute a small number of vibrational levels with an ultrasmall basis set without a potential function. To test the ideas, parametrized uncoupled and coupled Gaussian functions as well as direct-product and coupled Hermite basis sets are used to compute four low-lying vibrational energy levels of H2O on model harmonic and anharmonic uncoupled (polynomial) potential energy surfaces. In addition, we compute levels directly from ab initio points and thereby include all coupling and anharmonicity. We conclude that uncoupled parametrized Gaussian and Hermite functions are a good choice for anharmonic and coupled problems.

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 score0.294
Threshold uncertainty score0.325

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 head0.060
GPT teacher head0.342
Teacher spread0.283 · 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

Citations26
Published2012
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Chemical Theory and ComputationSame topicSpectroscopy and Quantum Chemical StudiesFrench-language works237,207