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Record W2121004699 · doi:10.1504/ijamc.2009.026849

Rapid impingement detection and surface distance measurement system for real-time ball-and-socket joint motion simulation

2009· article· en· W2121004699 on OpenAlex
Ding Cai, Won Sook Lee, Chris Joslin, Paul E. Beaulé

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.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueInternational Journal of Advanced Media and Communication · 2009
Typearticle
Languageen
FieldMedicine
TopicHip disorders and treatments
Canadian institutionsUniversity of Ottawa
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsComputer scienceBall (mathematics)Joint (building)KinematicsMotion captureMotion analysisComputer visionArtificial intelligenceSimulationMotion (physics)GeometryMathematicsPhysicsEngineering

Abstract

fetched live from OpenAlex

Detecting the position and the level of joint impingement is often a key to computer-aided surgical plan to normalise joint kinematics. So far for ball-and-socket joint, most of the up-to-date impingement detection methods are not efficient or only consider a few collided points as the detection results. In this paper, we present a real-time impingement detection system with rapid geometry sampling and surface-to-surface distance measurement feature for joint motion simulation. This is an expanded version of a paper presented at the 3rd IEEE International Workshop on Medical Measurements and Applications, 9?10 May 2008, Ottawa, ON, Canada.

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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.913
Threshold uncertainty score0.326

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 head0.027
GPT teacher head0.297
Teacher spread0.270 · 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