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Record W6987700743

Towards the development of a sub 500 micron thermally actuated scanning fiber endoscope for detection of lung cancer

2018· dissertation· en· W6987700743 on OpenAlexfundno aff

Bibliographic record

VenueSummit (Simon Fraser University) · 2018
Typedissertation
Languageen
FieldEngineering
TopicSoft Robotics and Applications
Canadian institutionsnot available
FundersBC Cancer AgencySimon Fraser University
KeywordsActuatorEndoscopeDeflection (physics)Optical fiberLung cancerFiber
DOInot available

Abstract

fetched live from OpenAlex

Medical professionals increasingly rely on endoscopes to carry out many minimallyinvasive procedures on patients in order to safely examine, diagnose and treat a myriad of conditions.However, their distal tip size dictates which passages of the body they can be inserted into and consequently what organs they can access.For inaccessible areas and organs, patients are often subjected to intrusive, risky and uncomfortable procedures; diagnosis of lung cancer is one of these cases.Hence, this study sets out to design an endoscope head that has an outer diameter of less than 500 microns, small enough to be inserted into the lungs.To attain this goal, a novel approach based on resonance thermal excitation of a dual clad single mode optical fiber at a location close to its base is proposed.The previously obtained analytical models for describing the lateral vibratory motion of the fixed-free micro-cantilever are used to validate the corresponding physical prototypes.Parameters such as choice of materials, resonance frequency, bonding methods, shape and dimensions of the actuator bridge, structural rigidity, assembly are considered in the physical design of the device.Lateral free-end deflection of the center fiber is used as a benchmark for evaluating performance.The results show that this novel proposal can be used to satisfy the project requirements.

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 score0.001
Threshold uncertainty score0.003

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)0.0010.000

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 head0.012
GPT teacher head0.228
Teacher spread0.216 · 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
Published2018
Admission routes1
Has abstractyes

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