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Record W2058559875 · doi:10.1364/oe.19.025161

Vertical optical sectioning using a magnetically driven confocal microscanner aimed for in vivo clinical imaging

2011· article· en· W2058559875 on OpenAlex
Hadi Mansoor, Haishan Zeng, Keqin Chen, Yingqiu Yu, Jianhua Zhao, Mu Chiao

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 · 2011
Typearticle
Languageen
FieldEngineering
TopicOptical Coherence Tomography Applications
Canadian institutionsBC Cancer AgencyUniversity of British Columbia
FundersCanadian Institutes of Health Research
KeywordsMaterials scienceOpticsConfocalMicrolensOptical sectioningConfocal microscopyLaserWaferOptical axisOptical fiberSurface micromachiningTransverse planeOptoelectronicsLens (geology)Physics

Abstract

fetched live from OpenAlex

This paper presents a confocal microscanner for direct vertical optical sectioning of biological samples. Confocal imaging is performed by transverse (X-axis) and axial (Z-axis) scanning of a focused laser beam using an optical fiber and a microlens respectively. The actuators are fabricated by laser micromachining techniques and are driven by electromagnetic forces. Optical and mechanical performance of the system is predicted by simulation software packages and characterized by experimental measurements. The scanner has lateral resolution of 3.87 µm and axial resolution of 10.68 µm with a field of view of 145 µm in X and 190 µm in Z directions. Confocal imaging of a polymer layer deposited on a silicon wafer and onion epidermal cells is demonstrated.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.934
Threshold uncertainty score1.000

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 head0.038
GPT teacher head0.291
Teacher spread0.253 · 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