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Record W2102602383 · doi:10.1115/imece2003-43979

Measurements of the Residual Stresses Due to Cement Polymerization for Cemented Hip Implants

2003· article· en· W2102602383 on OpenAlexaff
Natalia Nun ̃o, D. Plamondon

Bibliographic record

VenueAdvances in Bioengineering · 2003
Typearticle
Languageen
FieldMedicine
TopicOrthopaedic implants and arthroplasty
Canadian institutionsUniversité du Québec
Fundersnot available
KeywordsMaterials scienceCementBone cementComposite materialResidual stressImplantPolymethyl methacrylateCuring (chemistry)ProsthesisBiomedical engineeringPolymerSurgery

Abstract

fetched live from OpenAlex

In cemented hip implant, the polymethyl methacrylate (PMMA) also called bone cement is used as grouting material between the implant and the bone. During the operation, the bone cement still in a liquid form is inserted between the femoral component and the bone. During polymerisation of the cement, residual stresses are generated in the bulk cement. The process of cement curing is a complex solidification phenomenon where transient stresses are generated and the residual stresses vary with different boundary conditions during curing (Ahmed et al., 1982). In particular, normal stresses are generated at the implant-PMMA interface resulting in a press-fit problem. The cement does not have a chemical bond with the stem nor the bone, however it fills completely the space between the two and serves to distribute the load being transferred from the stem to the bone. An experiment has been devised to measure directly the residual stresses of the bone cement to reproduce the in-vivo behaviour of the prosthesis. An idealized prosthesis (19-mm diameter) is used. A subminiature load cell (9.5-mm diameter) is inserted inside the stem to measure directly the radial residual stresses of the PMMA on the stem. Bone cement polymerizes between the stem and the synthetic bone (40-mm outside diameter). The tests are conducted at body temperature of 37°C.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.618
Threshold uncertainty score0.296

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 head0.024
GPT teacher head0.284
Teacher spread0.260 · 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 designBench or experimental
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
Published2003
Admission routes1
Has abstractyes

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