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Record W4386766113 · doi:10.2106/jbjs.22.00805

Applications of Extended Reality in Orthopaedic Surgery

2023· article· en· W4386766113 on OpenAlexaff
Ehab M. Nazzal, Bálint Zsidai, Laurie A. Hiemstra, Sébastien Lustıg, Kristian Samuelsson, Volker Musahl

Bibliographic record

VenueJournal of Bone and Joint Surgery · 2023
Typearticle
Languageen
FieldMedicine
TopicSurgical Simulation and Training
Canadian institutionsBanff CentreUniversity of Calgary
Fundersnot available
KeywordsAugmented realityVirtual realityModalitiesMixed realityArtificial realityComputer-mediated realityComputer scienceHuman–computer interactionMedicineSociology

Abstract

fetched live from OpenAlex

➤ Extended reality is a term that encompasses different modalities, including virtual reality, augmented reality, and mixed reality.➤ Although fully immersive virtual reality has benefits for developing procedural memory and technical skills, augmented and mixed reality are more appropriate modalities for preoperative planning and intraoperative utilization.➤ Current investigations on the role of extended reality in preoperative planning and intraoperative utilization are still in the early stages, but preliminarily show that extended reality technologies can help surgeons to be more accurate and efficient.

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)0.003
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.293
Threshold uncertainty score0.212

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
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 head0.073
GPT teacher head0.320
Teacher spread0.247 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations13
Published2023
Admission routes1
Has abstractyes

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