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Record W2171682620 · doi:10.1109/memsys.2011.5734596

A confocal fiber optic catheter for in vivo thickness measurement of biological tissues

2011· article· en· W2171682620 on OpenAlexafffund
H. Mansoor, Haishan Zeng, Mu Chiao

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicOptical Coherence Tomography Applications
Canadian institutionsBC Cancer AgencyUniversity of British Columbia
FundersBC Cancer AgencyUniversity of British Columbia
KeywordsConfocalMicrolensMaterials scienceBiomedical engineeringMicroelectromechanical systemsOptical fiberScannerOpticsCorneaConfocal microscopyBiological tissueOptoelectronicsLens (geology)Medicine

Abstract

fetched live from OpenAlex

A fiber optic catheter with a MEMS (Microelectromechanical Systems) scanning microlens is demonstrated in this paper. Biological tissue thickness measurement using confocal scanning is presented. The catheter has an outer diameter and a rigid length of 4.75 mm and 30 mm respectively. Thickness of biological tissue is measured by out-of-plane actuation of the microlens using a micro magnetic actuator and collecting the intensity of the reflected light from the tissue. Scanning is performed at the resonant frequency, eliminating signal artifacts due to the external vibrations and patient's involuntary movements. To demonstrate the functionality of the confocal scanner, cornea and skin thicknesses of a 5-months-old female C3H/HeN mouse were measured and compared with histology images.

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 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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.585
Threshold uncertainty score0.866

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)0.0010.000

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 head0.080
GPT teacher head0.260
Teacher spread0.180 · 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 teacher head, 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
Published2011
Admission routes2
Has abstractyes

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