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Record W4415126892 · doi:10.1115/1.4070110

Development of a Novel Virtual Foot and Ankle Model for Surgical Education and Preoperative Planning

2025· article· en· W4415126892 on OpenAlexaff
Hannah Seatle, Thomas Looi, Santhija Jegatheeswaran, Maryse Bouchard

Bibliographic record

VenueJournal of Medical Devices · 2025
Typearticle
Languageen
FieldMedicine
TopicSurgical Simulation and Training
Canadian institutionsSickKids FoundationCanada Research ChairsUniversity of TorontoHospital for Sick Children
Fundersnot available
KeywordsAnkleFoot (prosody)BiomechanicsWork (physics)ReplicateSurgical planningVirtual realityFoot and ankle surgery

Abstract

fetched live from OpenAlex

Abstract This paper reports on a promising proof of concept for a novel interactive computer application that can simulate a specific patient's foot deformity and causative underlying condition, then simulate realistic surgical corrective foot and ankle (FA) procedures enabling clinicians to predict how their patient's anatomy will respond intra-operatively to different treatment options. This model is being developed with the goal of establishing better standards of care for foot and ankle surgery and allowing clinicians to preoperatively determine the optimal surgical procedures for each patient. The purpose of this paper is to describe the initial design of this foot model, which uses the Unity game engine to simulate human foot biomechanics. Preliminary results indicate that the current virtual model prototype can replicate normal foot biomechanics with reasonable fidelity; however, future work is still required to refine model parameters, and extensive validation is required to prove clinical accuracy.

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)0.001
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 score0.894
Threshold uncertainty score0.172

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.058
GPT teacher head0.391
Teacher spread0.333 · 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
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

Citations1
Published2025
Admission routes1
Has abstractyes

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