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Record W1973676032 · doi:10.1115/sbc2008-192176

Secondary Stability of a Composite Biomimetic Cementless Hip Stem

2008· article· en· W1973676032 on OpenAlexaff
Christiane Caouette, Martin Bureau, L’Hocine Yahia

Bibliographic record

VenueASME 2008 Summer Bioengineering Conference, Parts A and B · 2008
Typearticle
Languageen
FieldMedicine
TopicOrthopaedic implants and arthroplasty
Canadian institutionsNational Research Council CanadaPolytechnique Montréal
Fundersnot available
KeywordsStress shieldingOsseointegrationMaterials scienceOsteolysisImplantProsthesisBone resorptionBiomedical engineeringPopulationDentistrySurgeryMedicine

Abstract

fetched live from OpenAlex

Total hip replacement is one of the most successful and frequent surgery in the world; over a million of these procedures are performed every year, and the numbers are growing with the ageing of the general population. The patients who receive these implants also are younger nowadays. Major problems however still subsist with traditional hip stems: aseptic loosening is a common cause of revision surgery. The main causes of aseptic loosening are both mechanical and biological in origin. Mechanical causes include stress shielding and micromotions at bone-implant interface, and biological causes are mainly osteolysis triggered by wear debris formation and bone remodeling. To remedy the mechanical issues, a biomimetic concept was developed (patent pending): an osseointegrated stem with mechanical properties close to those of the surrounding bone would avoid both stress shielding and micromotions phenomena. To evaluate this concept, a finite element model (FEM) was developed and used to simulate bone resorption, stress shielding and micromotions [1]. The preliminary results were promising as those problems were significantly reduced with the new prosthesis, but the model still remained to be proved accurate; its bone-implant interface was of particular interest because of its decisive influence on micromotions.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.064
Threshold uncertainty score0.714

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.048
GPT teacher head0.245
Teacher spread0.198 · 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

Citations0
Published2008
Admission routes1
Has abstractyes

Explore more

Same venueASME 2008 Summer Bioengineering Conference, Parts A and BSame topicOrthopaedic implants and arthroplastyFrench-language works237,207