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Record W4210250071 · doi:10.1117/12.2610457

OCT-guided contour scanning for dynamically-focused photoacoustic remote sensing microscopy

2022· article· en· W4210250071 on OpenAlexaff
Matthew T. Martell, Nathaniel J. M. Haven, Sveta Silverman, Lashan Peiris, Jean Deschênes, Roger J. Zemp

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicPhotoacoustic and Ultrasonic Imaging
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMaterials scienceMicroscopyBiomedical engineeringOpticsPhysicsMedicine

Abstract

fetched live from OpenAlex

Ultraviolet photoacoustic remote sensing (UV-PARS) microscopy is a non-contact imaging modality capable of producing label-free absorption contrast images of cell nuclei. This virtual hematoxylin-like imaging combined with virtual eosin-like data from 1310 nm scattering microscopy can provide complete virtual H&E histologically in unstained tissues. Here, we develop contour scanning for applying UV-PARS and scattering-based virtual histology in fresh and formalin-fixed thick tissues. Our spectral-domain OCT-guided approach initially scans specimens in 3D, and a custom algorithm extracts the surface contour. A high-resolution UV-PARS scan is then performed using a z-axis stage for dynamic focusing to compensate for sample surface irregularities.

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)0.001
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: none
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0010.000

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 head0.013
GPT teacher head0.245
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

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

Citations0
Published2022
Admission routes1
Has abstractyes

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