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Record W2046864679 · doi:10.1115/1.1471531

An Endoscopic and Robotic Tooth-like Compliance and Roughness Tactile Sensor

2002· article· en· W2046864679 on OpenAlex

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 Mechanical Design · 2002
Typearticle
Languageen
FieldEngineering
TopicAdvanced Sensor and Energy Harvesting Materials
Canadian institutionsConcordia University
Fundersnot available
KeywordsTactile sensorPolyvinylidene fluorideMeasure (data warehouse)Surface roughnessSurface finishDeformation (meteorology)Robot end effectorFabricationAcousticsRobotMechanical engineeringMaterials scienceComputer scienceArtificial intelligenceEngineeringComposite material

Abstract

fetched live from OpenAlex

This paper reports on design, fabrication and testing of a prototype Polyvinylidene Fluoride (PVDF) tactile sensor for endoscopic and robotic applications. The sensor can measure both compliance and surface roughness. It consists of rigid and compliant elements. A relative deformation between adjacent parts of the contact object is used to measure the compliance, and the deformation of the compliant element of the sensor is used to measure the profile of a rough surface. The sensor in miniaturized form can be integrated with both endoscopic graspers and robotic end effectors. The theoretical analysis of the sensor is made and compared with experimental values. The advantages and limitations of the sensor are also discussed.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.690
Threshold uncertainty score0.465

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 head0.059
GPT teacher head0.257
Teacher spread0.198 · 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