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Record W4214869577 · doi:10.5435/jaaos-d-21-00964

Augmented Reality in Arthroplasty: An Overview of Clinical Applications, Benefits, and Limitations

2022· review· en· W4214869577 on OpenAlexaff
Michael Tänzer, Carl Laverdière, Bardia Barimani, Adam Hart

Bibliographic record

VenueJournal of the American Academy of Orthopaedic Surgeons · 2022
Typereview
Languageen
FieldMedicine
TopicSurgical Simulation and Training
Canadian institutionsMcGill UniversityObject Research Systems (Canada)
Fundersnot available
KeywordsWorkflowAugmented realityMedicineField (mathematics)ArthroplastyPosition (finance)Extension (predicate logic)Human–computer interactionMedical physicsComputer scienceSurgeryDatabase

Abstract

fetched live from OpenAlex

Augmented reality (AR) is a natural extension of computer-assisted surgery whereby a computer-generated image is superimposed on the surgeon's field of vision to assist in the planning and execution of the procedure. This emerging technology shows great potential in the field of arthroplasty, improving efficiency, limb alignment, and implant position. AR has shown the capacity to build on computer navigation systems while providing more elaborate information in a streamlined workflow to the user. This review investigates the current uses of AR in the field of arthroplasty and discusses outcomes, limitations, and potential future directions.

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 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)0.004
metaresearch head score (Gemma)0.002
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: Review · Consensus signal: Review
Teacher disagreement score0.972
Threshold uncertainty score0.684

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0000.002
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
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 head0.332
GPT teacher head0.473
Teacher spread0.140 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
Domainnot available
GenreReview

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

Citations19
Published2022
Admission routes1
Has abstractyes

Explore more

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