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Record W2126197966 · doi:10.1302/0301-620x.87b9.15710

Impact loading of articular cartilage during transplantation of osteochondral autograft

2005· article· en· W2126197966 on OpenAlexaff
R. A. Whiteside, R. P. Jakob, U.P. Wyss, Pierre Mainil‐Varlet

Bibliographic record

VenueJournal of Bone and Joint Surgery - British Volume · 2005
Typearticle
Languageen
FieldMedicine
TopicOsteoarthritis Treatment and Mechanisms
Canadian institutionsQueen's University
Fundersnot available
KeywordsArticular cartilageFEMORAL CONDYLECartilageChondrocyteTransplantationArticular cartilage repairMedicineArticular surfaceSurgeryDegeneration (medical)Cartilage damageCondyleAutologous chondrocyte implantationMaterials scienceBiomedical engineeringAnatomyOsteoarthritisPathology

Abstract

fetched live from OpenAlex

Surgical reconstruction of articular surfaces by transplantation of osteochondral autografts has shown considerable promise in the treatment of focal articular lesions. During mosaicplasty, each cylindrical osteochondral graft is centred over the recipient hole and delivered by impacting the articular surface. Impact loading of articular cartilage has been associated with structural damage, loss of the viability of chondrocytes and subsequent degeneration of the articular cartilage. We have examined the relationship between single-impact loading and chondrocyte death for the specific confined-compression boundary conditions of mosaicplasty and the effect of repetitive impact loading which occurs during implantation of the graft on the resulting viability of the chondrocytes. Fresh bovine and porcine femoral condyles were used in this experiment. The percentage of chondrocyte death was found to vary logarithmically with single-impact energy and was predicted more strongly by the mean force of the impact rather than by the number of impacts required during placement of the graft. The significance of these results in regard to the surgical technique and design features of instruments for osteochondral transplantation is discussed.

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 score0.383
Threshold uncertainty score0.492

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
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 head0.010
GPT teacher head0.228
Teacher spread0.218 · 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

Citations72
Published2005
Admission routes1
Has abstractyes

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