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Record W2063999040 · doi:10.1063/1.1764499

Absolute intensities of Raman trace scattering from bicyclo-[1.1.1]-pentane

2004· article· en· W2063999040 on OpenAlexaff
Richard Dawes, Kathleen Gough

Bibliographic record

VenueThe Journal of Chemical Physics · 2004
Typearticle
Languageen
FieldChemistry
TopicAdvanced NMR Techniques and Applications
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsAnharmonicityPentaneChemistryIntensity (physics)Fermi resonanceResonance (particle physics)Raman spectroscopyRaman scatteringMolecular physicsAnalytical Chemistry (journal)Atomic physicsPhysicsOpticsCondensed matter physicsOrganic chemistry

Abstract

fetched live from OpenAlex

Our previous theoretical studies have identified the Raman intensity parameter for the bridgehead C-H stretch in bicyclo-[1.1.1]-pentane as the largest for any saturated hydrocarbon yet considered, while the methylene C-H parameter is predicted to be ordinary. Theoretical methods including self-consistent field, static and time dependent density functional theory, and coupled cluster, all predict a large bridgehead intensity parameter, but differ widely in the actual value. We have synthesized bicyclo-[1.1.1]-pentane and recorded the absolute intensity Raman trace scattering spectra. The recorded intensity of a resonance polyad in the C-H stretching region has been resolved and distributed onto the fundamental modes through an anharmonic resonance analysis from a computed quartic force field. The experimental internal coordinate intensity parameters have been obtained and compared with those computed. Although the static and dynamic density functional values overestimate the parameter by 10%-18%, the values predicted at the coupled-cluster level are found to be correct to within experimental error.

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)0.000
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.015
GPT teacher head0.264
Teacher spread0.249 · 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 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

Citations4
Published2004
Admission routes1
Has abstractyes

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