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Record W2117445881 · doi:10.1177/0021998308096331

A Fatigue Damage Model for the Fiber-reinforced Composite of Haversian Cadaveric Cortical Bone

2008· article· en· W2117445881 on OpenAlexafffund
A. Varvani‐Farahani, Hussain Najmi

Bibliographic record

VenueJournal of Composite Materials · 2008
Typearticle
Languageen
FieldDentistry
TopicDental Implant Techniques and Outcomes
Canadian institutionsToronto Metropolitan University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMaterials scienceOsteonComposite materialCortical boneComposite numberCadaveric spasmFiberStiffnessElastic modulusStress (linguistics)Anatomy

Abstract

fetched live from OpenAlex

A model is developed to assess the fatigue damage of cadaveric human cortical bone as a fiber-reinforced composite by incorporating stiffness degradation of bone materials as the number of loading cycles progresses. This study characterizes the cortical bone structure as a natural fiber-reinforced composite material consisting of Haversian osteons (fibers) embedded in interstitial bone (matrix) and separated by weak cement-line interfaces. The proposed damage model included such mechanical and histological parameters as osteon volume fraction, donor age, cyclic stress magnitude, secant modulus of osteons, and cement line interfacial strength. Predicted fatigue damage results were found in good agreement with several experimentally obtained damage results of cortical bone samples tested by different laboratories.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.043
Threshold uncertainty score0.538

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.049
GPT teacher head0.310
Teacher spread0.261 · 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
Published2008
Admission routes2
Has abstractyes

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