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Biomechanical Analysis on Vancouver Periprosthetic Fracture in Femur Using the Finite Element Modeling

2022· book-chapter· en· W4226412907 on OpenAlexaboutno aff
Raja Dhason, Sandipan Roy, Shubhabrata Datta

Bibliographic record

VenueAdvances in mechatronics and mechanical engineering (AMME) book series · 2022
Typebook-chapter
Languageen
FieldMedicine
TopicOrthopaedic implants and arthroplasty
Canadian institutionsnot available
Fundersnot available
KeywordsPeriprostheticFixation (population genetics)FemurFemur fractureFemoral fractureImplantOrthodonticsFinite element methodMedicineProsthesisFracture (geology)ArthroplastySurgeryEngineeringStructural engineeringGeotechnical engineering

Abstract

fetched live from OpenAlex

After total hip arthroplasty (THA), high demands occur in the femoral fixation, especially for elderly patients due to periprosthetic fractures. Fractures happened in the femur after THA was classified based on Vancouver periprosthetic femoral fracture. Choosing the fixation for these types of specific fracture types are challenging due to pattern and orientation of the fracture in the THA prosthesis. Several researchers have reported the clinical, experimental, and computational studies about the failure of fixation methods, and they highlighted the remedies and scope in the further studies. Most of the authors recommended the computational studies having the advantage to predict the inner behaviour of the bone because invivo/invitro study availability of the specimen are limited and it needs ethical clearance. The current study focussed on computational studies in periprosthetic fractures and aims to discuss the three dimensional model creation, mesh generation, material properties, boundary conditions/loading, limitation, opinions, and future thoughts in implant design.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.714
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0010.000

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 head0.009
GPT teacher head0.236
Teacher spread0.227 · 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.

Study designSimulation or modeling
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

Citations0
Published2022
Admission routes1
Has abstractyes

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