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Record W2044199834 · doi:10.1364/oe.21.010095

Extended depth of field microscopy for rapid volumetric two-photon imaging

2013· article· en· W2044199834 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueOptics Express · 2013
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdvanced Fluorescence Microscopy Techniques
Canadian institutionsUniversité Laval
FundersCanadian Institutes of Health ResearchHealth Canada
KeywordsOpticsMicroscopyDepth of fieldMaterials scienceLight sheet fluorescence microscopyMicroscopeResolution (logic)Image resolutionTwo-photon excitation microscopyFluorescence microscopeOptical microscopePhotonVolume (thermodynamics)Temporal resolutionNear-field scanning optical microscopeField of viewScanning confocal electron microscopyFluorescenceScanning electron microscopePhysicsComputer scienceArtificial intelligence

Abstract

fetched live from OpenAlex

Two-photon fluorescence microscopy is an influential tool in biology, providing valuable information on the activity of cells deep inside the tissue. However, it is limited by its low speed for imaging volume samples. Here we present the design of a two-photon scanning microscope with an extended and adjustable depth of field, which improves the temporal resolution for sampling thick samples. Moreover, this method implies no loss of optical power and resolution, and can be easily integrated into most commercial laser-scanning microscopy systems. We demonstrate experimentally the gain in performance of the system by comparing volumetric scans of neuronal structures with a standard versus an extended depth of field system.

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.

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: Methods · Consensus signal: none
Teacher disagreement score0.235
Threshold uncertainty score0.704

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 head0.008
GPT teacher head0.293
Teacher spread0.285 · 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