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Record W1580862337 · doi:10.1002/0470027320.s0501

Linear Dichroism in Infrared Spectroscopy

2001· other· en· W1580862337 on OpenAlexaff
Thierry Buffeteau, Michel Pézolet

Bibliographic record

VenueHandbook of Vibrational Spectroscopy · 2001
Typeother
Languageen
FieldChemistry
TopicMolecular spectroscopy and chirality
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsLinear dichroismPolarizerInfraredAnisotropyDichroismPolarization (electrochemistry)OpticsMaterials scienceLinear polarizationInfrared spectroscopyPerpendicularSpectroscopyOrientation (vector space)Molecular physicsChemistryBirefringenceCircular dichroismPhysicsCrystallographyLaser

Abstract

fetched live from OpenAlex

Abstract The absorption of linearly polarized infrared radiation by oriented samples is sensitive to the state of polarization of the incident radiation. This phenomenon is known as the infrared linear dichroism (IRLD). The degree of optical anisotropy in oriented samples can be characterized by measuring two spectra using light polarized parallel and perpendicular to a reference direction. In this chapter, the theoretical expressions allowing the quantitative determination of molecular orientation from IRLD measurements for systems showing both uniaxial and biaxial symmetry of orientation are described. In addition, typical examples of the use of IRLD to determine the orientation of polymers and biological membranes are presented. These results were obtained from either static measurements using normal or oblique incidence or dynamic measurements using a rotating polarizer or a photoelastic modulator (PM‐IRLD). The high sensitivity of PM‐IRLD allows following the kinetics of orientation over a short timescale.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.012
Threshold uncertainty score0.041

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.003
Science and technology studies0.0010.002
Scholarly communication0.0020.002
Open science0.0020.002
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0120.010

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 head0.008
GPT teacher head0.264
Teacher spread0.256 · 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 designNot applicable
Domainnot available
GenreMethods

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

Citations8
Published2001
Admission routes1
Has abstractyes

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