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Record W2150168975 · doi:10.1364/oe.19.004357

Blood cell assisted in vivo Particle Image Velocimetry using the confocal laser scanning microscope

2011· article· en· W2150168975 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.

Bibliographic record

VenueOptics Express · 2011
Typearticle
Languageen
FieldPhysics and Astronomy
TopicDigital Holography and Microscopy
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsConfocalConfocal microscopyMicroscopeParticle image velocimetryVelocimetryParticle tracking velocimetryOpticsMaterials scienceMicroscopyIn vivoBiomedical engineeringBlood flowCapillary actionPhysicsBiologyMedicine

Abstract

fetched live from OpenAlex

We demonstrated the feasibility of blood cell assisted in vivo Particle Image Velocimetry using confocal microscopy. Blood flow of skin vessel in a mouse was non-invasively imaged in vivo using a confocal microscopy. The video-rate confocal microscope was used to monitor the motion of the blood cells in the capillary of a live mouse ear. The home-built confocal laser scanning microscopy allowed us to take images at the acquisition rate of 30 frames per second. The individual blood cells could be distinguished from other cells and the trajectory of the each cell could be followed in the sequential images. The acquired confocal images were used to get the velocity profile of the in vivo blood flow in conjunction with the Particle Image Velocimetry (PIV), without injecting any exogenous nano/micro particles into the mouse. We were able to measure the blood velocity up to a few hundreds µm/sec for various vessels in a live mouse. Because there is no need for the injection of the exogenous tracing particles, it is expected that we could apply the current technology to the study of human capillary blood stream.

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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.043
Threshold uncertainty score0.514

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 head0.021
GPT teacher head0.253
Teacher spread0.232 · 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