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Record W2048470656 · doi:10.1115/1.4023264

High Sensitive Force Sensing Based on the Optical Fiber Coupling Loss

2013· article· en· W2048470656 on OpenAlex
Roozbeh Ahmadi, Muthukumaran Packirisamy, Javad Dargahi

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.

Bibliographic record

VenueJournal of Medical Devices · 2013
Typearticle
Languageen
FieldEngineering
TopicAdvanced Fiber Optic Sensors
Canadian institutionsConcordia University
Fundersnot available
KeywordsMicrosystemOptical fiberMaterials scienceSensitivity (control systems)Fiber optic sensorComputer scienceAcousticsElectronic engineeringEngineeringPhysicsTelecommunicationsNanotechnology

Abstract

fetched live from OpenAlex

In the present paper, an innovative miniaturized optical force sensor is introduced for use in medical devices such as minimally invasive robotic-surgery instruments. The sensing principle of the sensor relies on light transmission in optical fibers. Although the sensor is designed for use in surgical systems, it can be used in various other applications due to its novel features. The novelty of the sensor lies in offering four features in a single miniaturized package using a simple optical-based sensing principle. These four features are the high accuracy/resolution, the magnetic resonance compatibility, the electrical passivity, and the absence of drift in the measurement of continuous static force. The proposed sensor was micromachined using microsystems technology and tested. The sensor measures 18 mm, 4 mm, and 1 mm in length, width, and thickness, respectively. The sensor was calibrated and its performance under both static and dynamic loading conditions was investigated. The experimental test results demonstrate a 0.00–2.00 N force range with an rms error of approximately 2% of the force range. Its resolution is 0.02 N. The characteristics of the sensor such as its size, its measurement range, and its sensitivity are also easily tunable.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.039
Threshold uncertainty score0.602

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 integrity0.0000.001
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 head0.010
GPT teacher head0.235
Teacher spread0.226 · 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