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Record W2068632504 · doi:10.1109/tbme.2012.2236326

A Handheld Electromagnetically Actuated Fiber Optic Raster Scanner for Reflectance Confocal Imaging of Biological Tissues

2012· article· en· W2068632504 on OpenAlexafffund
Hadi Mansoor, Haishan Zeng, Isabella T. Tai, Jianhua Zhao, Mu Chiao

Bibliographic record

VenueIEEE Transactions on Biomedical Engineering · 2012
Typearticle
Languageen
FieldEngineering
TopicOptical Coherence Tomography Applications
Canadian institutionsCanada's Michael Smith Genome Sciences CentreBC Cancer AgencyUniversity of British Columbia
FundersBC Cancer AgencyCanadian Institutes of Health ResearchCanada's Michael Smith Genome Sciences Centre
KeywordsScannerMaterials scienceOpticsConfocalOptical fiberRaster graphicsRaster scanConfocal microscopyPerpendicularCantileverOptoelectronicsPhysicsComputer science

Abstract

fetched live from OpenAlex

We present a hand-held device aimed for reflectance-mode confocal imaging of biological tissues. The device consists of a light carrying optical fiber and a miniaturized raster scanner located at the distal end of the fiber. It is fabricated by mounting a polarization maintaining optical fiber on a cantilever beam that is attached to another beam such that their bending axes are perpendicular to each other. Fiber scanner is driven by electromagnetic forces and enables large fiber deflections with low driving currents. Optical resolutions of the system are 1.55 and 8.45 μm in the lateral and axial directions, respectively. Functionality of the system is demonstrated by obtaining confocal images of a fly wing and a human colon tissue sample.

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 score0.004
Threshold uncertainty score0.014

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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.244
Teacher spread0.231 · 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

Citations18
Published2012
Admission routes2
Has abstractyes

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