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Record W2810594098 · doi:10.1177/1071100718781863

Revision and Salvage Management: Proceedings of the International Consensus Meeting on Cartilage Repair of the Ankle

2018· article· en· W2810594098 on OpenAlexaff
Peter N. Mittwede, Christopher D. Murawski, Jakob Ackermann, Simon Görtz, Beat Hintermann, Hak Jun Kim, David B. Thordarson, Francesca Vannini, Alastair Younger, Samuel B. Adams, Carol L. Andrews, Chayanin Angthong, Jorge Batista, O Baur, Steve Bayer, Christoph Becher, Gregory C. Berlet, Lorraine A. T. Boakye, Alexandra J. Brown, Roberto Buda, James Calder, Gian Luigi Canata, Dominic S. Carreira, Thomas O. Clanton, Jari Dahmen, Pieter D’Hooghe, Christopher W. DiGiovanni, Malcolm E. Dombrowski, Mark C. Drakos, Richard D. Ferkel, Paulo N. F. Ferrao, Lisa A. Fortier, Mark Glazebrook, Eric Giza, Mohamed Gomaa, Amgad M. Haleem, Kamran S. Hamid, László Hangody, Charles P. Hannon, Daniël Haverkamp, Jay Hertel, MaCalus V. Hogan, Kenneth J. Hunt, Eoghan T. Hurley, Jón Karlsson, Stephen R. Kearns, John G. Kennedy, Gino M. M. J. Kerkhoffs, Siu Wah Kong, Sameh A. Labib, Kaj T. A. Lambers, Jin Woo Lee, Keun Bae Lee, Jeffrey S. Ling, Umile Giuseppe Longo, Alberto Marangon, Graham McCollum, Adam Mitchell, Stefan Nehrer, Philipp Niemeyer, Martin O’Malley, David O. Osei-Hwedieh, Jochen Paul, Christopher J. Pearce, Hélder Pereira, Adam Popchak, Marcelo Pires Prado, Steven M. Raikin, Mikel L. Reilingh, Benjamin B. Rothrauff, Lew C. Schon, Yoshiharu Shimozono, Helene Simpson, Niall A. Smyth, Carolyn M. Sofka, Pietro Spennacchio, James W. Stone, Martin Sullivan, Masato Takao, Yasuhito Tanaka, Rocky S. Tuan, Víctor Valderrábano, Christiaan J. A. van Bergen, C. Niek van Dijk, Pim A. D. van Dijk, Tanawat Vaseenon, Markus Walther, Martin Wiewiorski, Xiangyang Xu, Youichi Yasui, Ichiro Yoshimura, Zijun Zhang

Bibliographic record

VenueFoot & Ankle International · 2018
Typearticle
Languageen
FieldMedicine
TopicFoot and Ankle Surgery
Canadian institutionsSt. Paul's Hospital
Fundersnot available
KeywordsMedicineAnkleConsensus conferenceDelphi methodEvidence-based medicineDelphiStatement (logic)SurgeryAlternative medicineLawPolitical sciencePathologyComputer science

Abstract

fetched live from OpenAlex

BACKGROUND: The evidence supporting best practice guidelines in the field of cartilage repair of the ankle are based on both low quality and low levels of evidence. Therefore, an international consensus group of experts was convened to collaboratively advance toward consensus opinions based on the best available evidence on key topics within cartilage repair of the ankle. The purpose of this article was to report on the consensus statements on "Revision and Salvage Management" developed at the 2017 International Consensus Meeting on Cartilage Repair of the Ankle. METHODS: Seventy-five international experts in cartilage repair of the ankle representing 25 countries and 1 territory were convened and participated in a process based on the Delphi method of achieving consensus. Questions and statements were drafted within 11 working groups focusing on specific topics within cartilage repair of the ankle, after which a comprehensive literature review was performed and the available evidence for each statement was graded. Discussion and debate occurred in cases where statements were not agreed on in unanimous fashion within the working groups. A final vote was then held, and the strength of consensus was characterized as follows: consensus, 51% to 74%; strong consensus, 75% to 99%; unanimous, 100%. RESULTS: A total of 8 statements on revision and salvage management reached consensus during the 2017 International Consensus Meeting on Cartilage Repair of the Ankle. One achieved unanimous support and 7 reached strong consensus (greater than 75% agreement). All statements reached at least 85% agreement. CONCLUSIONS: This international consensus derived from leaders in the field will assist clinicians with revision and salvage management in the cartilage repair of the ankle.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.138
Threshold uncertainty score0.296

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.016
GPT teacher head0.261
Teacher spread0.246 · 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 designObservational
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

Citations17
Published2018
Admission routes1
Has abstractyes

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