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Record W2141040792 · doi:10.1243/09544119jeim281

A navigation system for shoulder arthroscopic surgery

2007· article· en· W2141040792 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

VenueProceedings of the Institution of Mechanical Engineers Part H Journal of Engineering in Medicine · 2007
Typearticle
Languageen
FieldComputer Science
TopicAugmented Reality Applications
Canadian institutionsQueen's University
FundersNational Institutes of Health
KeywordsLandmarkScapulaComputer visionArthroscopyArtificial intelligenceMedicineNavigation systemComputer scienceCalibrationInterface (matter)SurgeryMathematics

Abstract

fetched live from OpenAlex

The general framework and experimental validation of a novel navigation system designed for shoulder arthroscopy are presented. The system was designed to improve the surgeon's perception of the three-dimensional space within the human shoulder. Prior to surgery, a surface model of the shoulder was created from computed tomography images. Intraoperatively, optically tracked arthroscopic instruments were calibrated. The surface model was then registered to the patient using tracked freehand ultrasound images taken from predefined landmark regions on the scapula. Three-dimensional models of the surgical instruments were displayed, in real time, relative to the surface model in a user interface. Laboratory experiments revealed only small registration and calibration errors, with minimal time needed to complete the intraoperative tasks.

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)0.003
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.901
Threshold uncertainty score0.358

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.023
GPT teacher head0.268
Teacher spread0.245 · 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