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Record W2055826616 · doi:10.1364/ol.36.002865

In vivo video rate multiphoton microscopy imaging of human skin

2011· article· en· W2055826616 on OpenAlexafffund
Anthony M. D. Lee, Hequn Wang, Yingqiu Yu, Shuo Tang, Jianhua Zhao, Harvey Lui, David I. McLean, Haishan Zeng

Bibliographic record

VenueOptics Letters · 2011
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdvanced Fluorescence Microscopy Techniques
Canadian institutionsVancouver Coastal HealthVancouver Coastal Health Research InstituteUniversity of British ColumbiaBC Cancer Agency
FundersBC Cancer AgencyCanadian Institutes of Health ResearchVGH and UBC Hospital FoundationCanadian Dermatology Foundation
KeywordsReticular DermisOpticsMicroscopyHuman skinFrame ratePixelMaterials scienceTwo-photon excitation microscopyImage resolutionPreclinical imagingSecond-harmonic generationFluorescence-lifetime imaging microscopyBiomedical engineeringFluorescenceIn vivoLaserDermisPhysicsMedicinePathology

Abstract

fetched live from OpenAlex

We present a multiphoton microscopy instrument specially designed for in vivo dermatological use that is capable of imaging human skin at 27 frames per second with 256 pixels × 256 pixels resolution without the use of exogenous contrast agents. Imaging at fast frame rates is critical to reducing image blurring due to patient motion and to providing practically short clinical measurement times. Second harmonic generation and two-photon fluorescence images and videos acquired at optimized wavelengths are presented showing cellular and tissue structures from the skin surface down to the reticular dermis.

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)0.000
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: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

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)0.0020.000

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 head0.009
GPT teacher head0.273
Teacher spread0.265 · 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

Citations37
Published2011
Admission routes2
Has abstractyes

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