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Record W3184844207 · doi:10.1186/s42649-021-00059-6

Multispectral intravital microscopy for simultaneous bright-field and fluorescence imaging of the microvasculature

2021· article· en· W3184844207 on OpenAlexafffund
G. Janssen, Mohamadreza Najiminaini, Yan Min Zhang, Parsa Omidi, Jeffrey J. L. Carson

Bibliographic record

VenueHan-guk hyeonmigyeong hakoeji/Applied microscopy · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdvanced Fluorescence Microscopy Techniques
Canadian institutionsSt Joseph's Health CareLawson Health Research InstituteLondon Health Sciences CentreWestern University
FundersSchulich School of Medicine and DentistryLawson Health Research Institute
KeywordsMicroscopyIntravital microscopyMicroscopeFluorescence microscopeMultispectral imageOptical microscopeContext (archaeology)FluorescenceMicrocirculationOpticsMaterials sciencePhysicsComputer scienceScanning electron microscopeBiologyArtificial intelligenceMedicine

Abstract

fetched live from OpenAlex

Intravital video microscopy permits the observation of microcirculatory blood flow. This often requires fluorescent probes to visualize structures and dynamic processes that cannot be observed with conventional bright-field microscopy. Conventional light microscopes do not allow for simultaneous bright-field and fluorescent imaging. Moreover, in conventional microscopes, only one type of fluorescent label can be observed. This study introduces multispectral intravital video microscopy, which combines bright-field and fluorescence microscopy in a standard light microscope. The technique enables simultaneous real-time observation of fluorescently-labeled structures in relation to their direct physical surroundings. The advancement provides context for the orientation, movement, and function of labeled structures in the microcirculation.

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 categoriesMeta-epidemiology (narrow)
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 score0.064
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.003
GPT teacher head0.252
Teacher spread0.249 · 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.

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

Citations5
Published2021
Admission routes2
Has abstractyes

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