MétaCan
Menu
Back to cohort
Record W2090066413 · doi:10.1364/ao.50.001798

Spectral domain fluorescence coherence phase microscopy

2011· article· en· W2090066413 on OpenAlexaff
Andra St. Quintin, Lukas-Karim Merhi, Marinko V. Šarunic

Bibliographic record

VenueApplied Optics · 2011
Typearticle
Languageen
FieldEngineering
TopicOptical Coherence Tomography Applications
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsOpticsMicroscopyCoherence (philosophical gambling strategy)Interference microscopyInterferometryMaterials scienceFluorescence microscopeNanoscopic scalePhase (matter)Interference (communication)Photoactivated localization microscopyOptical coherence tomographyFluorescenceSuper-resolution microscopyPhysicsNanotechnologyComputer science

Abstract

fetched live from OpenAlex

Spectral domain phase microscopy (SDPM) has been reported in the literature as a functional extension to low-coherence interferometry, which enables nanoscale measurement of a scatter's displacement. The signal in SDPM is generated from structural images that lack molecular specificity. This paper investigates the expansion of phase analysis to fluorescence self-interference signals to provide functional information about a sample. Spectral domain fluorescence coherence phase microscopy is demonstrated for nanoscale resolution motion detection of fluorescent particles with a signal-to-noise ratio limited resolution of ~10 nm. This paper demonstrates the feasibility of combining phase processing with fluorescence self-interference, which may be useful for future applications such as cell rheology.

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: none
Teacher disagreement score0.006
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.019
GPT teacher head0.245
Teacher spread0.226 · 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
Published2011
Admission routes1
Has abstractyes

Explore more

Same venueApplied OpticsSame topicOptical Coherence Tomography ApplicationsFrench-language works237,207