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Record W2059078498 · doi:10.1243/09544119jeim736

Evaluation of Synthetic Composite Tibias for Fracture Testing Using Impact Loads

2010· article· en· W2059078498 on OpenAlexafffund
Cheryl E. Quenneville, Gillian S. Greeley, C. Dunning

Bibliographic record

VenueProceedings of the Institution of Mechanical Engineers Part H Journal of Engineering in Medicine · 2010
Typearticle
Languageen
FieldMedicine
TopicBone fractures and treatments
Canadian institutionsGeneral Dynamics (Canada)Western University
FundersNatural Sciences and Engineering Research Council of CanadaGeneral Dynamics Land Systems
KeywordsComposite numberFracture (geology)Materials scienceStructural engineeringReliability engineeringOrthodonticsComputer scienceComposite materialEngineeringMedicine

Abstract

fetched live from OpenAlex

Composite synthetic bones are a commercially available substitute for cadaveric specimens, and they have previously been validated to replicate natural bone under quasistatic, non-destructive testing. Synthetic tibias could be used to analyse injury risk to the lower leg during impact events, but their failure mode must be validated by way of comparative tests to human bone. Synthetic tibias were instrumented with strain gauges and subjected to axial impact loading. Two different projectile masses were used for the tests, and the effects of force, momentum, and energy on failure were compared with previous cadaveric data. The composite tibias failed at forces between 37-45 per cent of those from cadavers, and failed via cortical delamination in combination with fracture. A Weibull analysis generated a survivability curve based on axial force at failure, and was shown to be lower than previous cadaveric curves. Failure was dependent on both the momentum and energy applied. Strain distributions through the synthetic tibias were significantly different from those of cadavers. The convex distal articular surface of the synthetic bones may partially account for the lower fracture tolerance. As a result of the many differences in response, these synthetic tibias are not recommended for use in impact fracture studies.

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)0.002
metaresearch head score (Gemma)0.005
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 score0.391
Threshold uncertainty score0.651

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.044
GPT teacher head0.325
Teacher spread0.281 · 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

Citations13
Published2010
Admission routes2
Has abstractyes

Explore more

Same venueProceedings of the Institution of Mechanical Engineers Part H Journal of Engineering in MedicineSame topicBone fractures and treatmentsFrench-language works237,207