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Record W2163240318 · doi:10.1002/jbio.201400116

Maintaining polarization in polarimetric multiphoton microscopy

2015· article· en· W2163240318 on OpenAlexafffund
Erik Bélanger, Raphaël Turcotte, Amy Daradich, Grégory Sadetsky, Pierre Gravel, Karine Bachand, Yves De Koninck, Daniel Côté

Bibliographic record

VenueJournal of Biophotonics · 2015
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicSpectroscopy Techniques in Biomedical and Chemical Research
Canadian institutionsUniversité LavalInstitut Universitaire en Santé Mentale de Québec
FundersNatural Sciences and Engineering Research Council of CanadaMultiple Sclerosis Society of Canada
KeywordsDichroic glassPolarimetryPolarization (electrochemistry)OpticsDichroic filterFluorescence anisotropyMicroscopyWavelengthPhysicsScatteringMaterials scienceChemistryFluorescence

Abstract

fetched live from OpenAlex

Polarimetric measurements in multiphoton microscopy can reveal information about the local molecular order of a sample. However, the presence of a dichroic through which the excitation beam propagates will generally scramble its polarization. We propose a simple scheme whereby a second properly‐oriented compensation dichroic is used to negate any alteration regardless of the wavelength and the initial polarization. We demonstrate how this robust and rapid approach simplifies polarimetric measurements in second‐harmonic generation, two‐photon excited fluorescence and coherent anti‐Stokes Raman scattering. Illustration of the polarization maintaining strategy with the compensating dichroic oriented such that its s ‐ and p ‐axes are interchanged with these of the primary dichroic. magnified image Illustration of the polarization maintaining strategy with the compensating dichroic oriented such that its s ‐ and p ‐axes are interchanged with these of the primary dichroic.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.035
Threshold uncertainty score0.346

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.018
GPT teacher head0.338
Teacher spread0.319 · 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

Citations8
Published2015
Admission routes2
Has abstractyes

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