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Record W2084204452 · doi:10.1364/oe.19.005902

Image formation in CARS microscopy: effect of the Gouy phase shift

2011· article· en· W2084204452 on OpenAlexafffund
Konstantin Popov, Adrian F. Pegoraro, Albert Stolow, Lora Ramunno

Bibliographic record

VenueOptics Express · 2011
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicSpectroscopy Techniques in Biomedical and Chemical Research
Canadian institutionsSteacie Institute for Molecular SciencesUniversity of Ottawa
FundersOntario Ministry of Research and InnovationNatural Sciences and Engineering Research Council of CanadaMitacsCanada Research Chairs
KeywordsOpticsMicroscopyPhase (matter)Interference microscopyMaterials scienceOptical microscopeDiffractionRefractive indexPhysicsScanning electron microscope

Abstract

fetched live from OpenAlex

Image formation in Coherent Anti-Stokes Raman Scattering (CARS) microscopy of sub-wavelength objects is investigated via a combined experimental, numerical and theoretical study. We consider a resonant spherical object in the presence of a nonresonant background, using tightly focused laser pulses. When the object is translated along the laser propagation axis, we find the CARS signal to be asymmetric about the laser focal plane. When the object is located before the focus, there is a distinct shadow within the image, whereas the brightest signal is obtained when the object is behind the focus. This behaviour is caused by interference between resonant and nonresonant signals, and the Gouy phase shift is responsible for the observed asymmetry within the image.

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)0.002
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 score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.011
GPT teacher head0.324
Teacher spread0.314 · 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

Citations23
Published2011
Admission routes2
Has abstractyes

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