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Record W2069532523 · doi:10.1053/jars.2001.19966

An investigation of 2 techniques for optimizing joint surface congruency using multiple cylindrical osteochondral autografts

2001· article· en· W2069532523 on OpenAlexafffund
Simon G. Pearce, Mark Hurtig, Richard Clarnette, Manpreet Kalra, Bryce J. Cowan, Anthony Miniaci

Bibliographic record

VenueArthroscopy The Journal of Arthroscopic and Related Surgery · 2001
Typearticle
Languageen
FieldMedicine
TopicOsteoarthritis Treatment and Mechanisms
Canadian institutionsUniversity of GuelphToronto Western Hospital
FundersUniversity Health Network
KeywordsMedicineFEMORAL CONDYLESurgeryJoint (building)CartilageArticular surfaceWeight-bearingBearing surfaceKnee JointArticular cartilageFemurAnatomyOsteoarthritis

Abstract

fetched live from OpenAlex

PURPOSE: To compare 2 techniques for optimizing joint congruency for miniature osteochondral autografting in the knee: intrinsic postoperative forces acting on overdrilled autografts protruding from the femur versus alignment by a surgeon at the time of grafting. TYPE OF STUDY: Controlled animal model experiment. METHODS: A full-thickness cartilage defect was created on the weight-bearing surface of the medial femoral condyle of 13 mature sheep. Three 4.5 x 10 mm cylindrical autografts were inserted into 14-mm deep recipient holes such that the grafts were held in place by side-wall friction alone. One treatment group received grafts that were delivered flush with the surrounding cartilage and the second group received grafts that were left 2-mm proud of the joint surface. RESULTS: Three months postoperatively, the proud grafts had been repositioned by weight bearing but perigraft fissuring and fibroplasia, and subchondral cavitations were serious complications. It is suspected that these complications were caused by excessive motion between the graft and recipient site in the proud grafts. CONCLUSIONS: Grafts should be delivered flush with the joint surface when performing osteochondral transfers to avoid graft micromotion and the consequent interference with graft integration and function.

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)0.001
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 score0.111
Threshold uncertainty score0.584

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.030
GPT teacher head0.285
Teacher spread0.255 · 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

Citations158
Published2001
Admission routes2
Has abstractyes

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