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Record W2509728136 · doi:10.1177/0363546516660064

International Meniscus Reconstruction Experts Forum (IMREF) 2015 Consensus Statement on the Practice of Meniscal Allograft Transplantation

2016· article· en· W2509728136 on OpenAlexaff
Alan Getgood, Robert F. LaPrade, Peter Verdonk, Wayne Gersoff, Brian J. Cole, Tim Spalding, Annunziato Amendola, Andrew A. Amis, Seong‐Il Bin, William D. Bugbee, David N.M. Caborn, Tom Carter, Kai‐Ming Chan, C Cohen, Moisés Cohen, Vincenzo Condello, Tom DeBerardino, Florian Dirisamer, Lars Engebretsen, Jack Farr, Andreas H. Gomoll, Chris Harner, Mark Heard, Laurie A. Hiemstra, Jin Goo Kim, J.M. Kim, Jong‐Min Kim, Elizaveta Kon, Koen Laggae, Bum‐Sik Lee, Robert Litchfield, Robert G. McCormack, Ian McDermott, Juan C. Monlau, Peter Myers, Frank R. Noyes, Christian Patsch, James Robinson, Scott Rodeo, Seung-Suk Seo, Seth L. Sherman, Rainer Siebold, Martyn Snow, Kevin R. Stone, Scott Tashman, Peter Thompson, Ewoud van Arkel, Willem van der Merwe, René Verdonk, Andy Williams, Stefano Zaffagnini

Bibliographic record

VenueThe American Journal of Sports Medicine · 2016
Typearticle
Languageen
FieldMedicine
TopicKnee injuries and reconstruction techniques
Canadian institutionsFowler Kennedy Sport Medicine ClinicWestern University
FundersAlloSourceSmith and NephewArthrexMusculoskeletal Transplant Foundation
KeywordsMeniscusStatement (logic)MedicineTransplantationSurgeryPhysical therapyPolitical scienceLaw

Abstract

fetched live from OpenAlex

Meniscal allograft transplantation (MAT) has become relatively commonplace in specialized sport medicine practice for the treatment of patients with a symptomatic knee after the loss of a functional meniscus. The technique has evolved since the 1980s, and long-term results continue to improve. However, there still remains significant variation in how MAT is performed, and as such, there remains opportunity for outcome and graft survivorship to be optimized. The purpose of this article was to develop a consensus statement on the practice of MAT from key opinion leaders who are members of the International Meniscus Reconstruction Experts Forum so that a more standardized approach to the indications, surgical technique, and postoperative care could be outlined with the goal of ultimately improving patient outcomes.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.053
metaresearch head score (Gemma)0.081
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.053
Threshold uncertainty score0.278

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0530.081
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.003
Bibliometrics0.0030.002
Science and technology studies0.0020.002
Scholarly communication0.0020.002
Open science0.0030.004
Research integrity0.0090.009
Insufficient payload (model declined to judge)0.0040.003

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 head0.310
Teacher spread0.300 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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

Citations144
Published2016
Admission routes1
Has abstractyes

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Same venueThe American Journal of Sports MedicineSame topicKnee injuries and reconstruction techniquesFrench-language works237,207