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Record W2996667552 · doi:10.1364/ol.45.000069

Multiplexed confocal microscope with a refraction window scanner and a single-photon avalanche photodiode array detector

2019· article· en· W2996667552 on OpenAlexafffund
Nehad Hirmiz, Anthony Tsikouras, Elizabeth J. Osterlund, Morgan Richards, David W. Andrews, Qiyin Fang

Bibliographic record

VenueOptics Letters · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdvanced Fluorescence Microscopy Techniques
Canadian institutionsCanada Research ChairsUniversity of TorontoMcMaster University
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health ResearchOntario Centres of Excellence
KeywordsOpticsAvalanche photodiodeConfocalDetectorMicroscopePhoton countingWindow (computing)ScannerPhotodiodeSingle-photon avalanche diodeConfocal microscopyMultiplexingMaterials sciencePhysics

Abstract

fetched live from OpenAlex

Currently, the spinning disk confocal microscope is the most popular fast confocal imaging system. However, these instruments require a high pixel density camera detector, limiting their use in many applications. We have designed a multiplexed confocal scheme that performs raster scanning of a <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"> <mml:mrow class="MJX-TeXAtom-ORD"> <mml:mn>32</mml:mn> <mml:mo>×</mml:mo> <mml:mn>32</mml:mn> </mml:mrow> </mml:math> foci array in which the output image is stationary after de-scanning. Our system can be coupled to a dense or sparse array detector, making it feasible to apply to rapid time-resolved photon counting, single-photon detection, and some super-resolution techniques.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.108
Threshold uncertainty score0.866

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.005
GPT teacher head0.217
Teacher spread0.212 · 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

Citations4
Published2019
Admission routes2
Has abstractyes

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