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Record W2041388143 · doi:10.2495/bio050251

The pressure generated during the insertion of an intramedullary device: experiments and numerical modeling

2005· article· en· W2041388143 on OpenAlexafffund
Daniel Dobrjanski, Omar Gaber, M. Ziad Saghir, Kamran Behdinan, Paul Zalzal, Justin de Beer, M. Papini

Bibliographic record

VenueWIT transactions on biomedicine and health · 2005
Typearticle
Languageen
FieldMedicine
TopicOrthopaedic implants and arthroplasty
Canadian institutionsJuravinski HospitalMount Sinai HospitalToronto Metropolitan University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsComputer science

Abstract

fetched live from OpenAlex

During the orthopaedic procedures of total knee arthroplasty (TKA) and total hip arthroplasty (THA), it is often necessary to hammer an intramedullary device into the femur.This action is thought to create high pressures in the intramedullary canal, and may result in the release of fat emboli into the cardiovascular system.This work presents measured intramedullary pressures generated during hammering of an intramedullary device into a simulated femur geometry consisting of a tube of porous open-cell plastic with the same porosity and pore size as femoral cortical bone.The experimental results were found to be, on average, approximately 20% lower than those predicted by a computational fluid dynamics (CFD) model of the insertion process.Based on this, we conclude that it is reasonable to use CFD models to predict intramedullary pressures resulting from orthopaedic procedures that breach the intramedullary canal.As far as the authors know, this is the first attempt to use CFD modeling to study a problem of this type.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
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 head0.030
GPT teacher head0.321
Teacher spread0.290 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations3
Published2005
Admission routes2
Has abstractyes

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Same venueWIT transactions on biomedicine and healthSame topicOrthopaedic implants and arthroplastyFrench-language works237,207