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Record W3188360837 · doi:10.1002/anie.202109345

Can One Measure Resonance Raman Optical Activity?

2021· article· en· W3188360837 on OpenAlexafffund
Guojie Li, Mutasem Alshalalfeh, Yanqing Yang, James R. Cheeseman, Petr Bouř, Yunjie Xu

Bibliographic record

VenueAngewandte Chemie International Edition · 2021
Typearticle
Languageen
FieldChemistry
TopicMolecular spectroscopy and chirality
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research ChairsCompute CanadaCanada Foundation for InnovationUniversity of AlbertaMinistry of Innovation and Advanced Education
KeywordsRaman spectroscopyRaman optical activityResonance (particle physics)Resonance Raman spectroscopyCoherent anti-Stokes Raman spectroscopySpectroscopyRaman scatteringChemistryMolecular physicsCircular dichroismNuclear magnetic resonanceCircular polarizationAnalytical Chemistry (journal)OpticsAtomic physicsPhysicsCrystallography

Abstract

fetched live from OpenAlex

Abstract Resonance Raman optical activity (RROA) is commonly measured as the difference in intensity of Raman scattered right and left circularly polarized light, I R −I L , when a randomly polarized light is in resonance with a chiral molecule. Strong and sometimes mono‐signate experimental RROA spectra of several chiral solutes were reported previously, although their signs and relative intensities could not be reproduced theoretically. By examining multiple light‐matter interaction events which can occur simultaneously under resonance, we show that a new form of chiral Raman spectroscopy, eCP‐Raman, a combination of electronic circular dichroism and circularly polarized Raman, prevails. By incorporating the finite‐lifetime approach for resonance, the experimental patterns of the model chiral solutes are captured theoretically by eCP‐Raman, without any RROA contribution. The results open opportunity for applications of eCP‐Raman spectroscopy and for extracting true RROA experimentally.

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)0.004
metaresearch head score (Gemma)0.013
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: none
Teacher disagreement score0.004
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.013
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0000.003
Scholarly communication0.0020.006
Open science0.0020.001
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0030.002

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 head0.263
Teacher spread0.245 · 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

Citations35
Published2021
Admission routes2
Has abstractyes

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