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Record W2811510543 · doi:10.1177/1071100718781866

Subchondral Pathology: Proceedings of the International Consensus Meeting on Cartilage Repair of the Ankle

2018· article· en· W2811510543 on OpenAlexaff
Yoshiharu Shimozono, Alexandra J. Brown, Jorge Batista, Christopher D. Murawski, Mohamed Gomaa, Siu Wah Kong, Tanawat Vaseenon, Masato Takao, Mark Glazebrook, Jakob Ackermann, Samuel B. Adams, Carol L. Andrews, Chayanin Angthong, O Baur, Steve Bayer, Christoph Becher, Gregory C. Berlet, Lorraine A. T. Boakye, 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, Eric Giza, Simon Görtz, Amgad M. Haleem, Kamran S. Hamid, László Hangody, Charles P. Hannon, Daniël Haverkamp, Jay Hertel, Beat Hintermann, MaCalus V. Hogan, Kenneth J. Hunt, Eoghan T. Hurley, Jón Karlsson, Stephen R. Kearns, John G. Kennedy, Gino M. M. J. Kerkhoffs, Hak Jun Kim, 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, Peter N. Mittwede, 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, Helene Simpson, Niall A. Smyth, Carolyn M. Sofka, Pietro Spennacchio, James W. Stone, Martin Sullivan, Yasuhito Tanaka, David B. Thordarson, Rocky S. Tuan, Víctor Valderrábano, Christiaan J. A. van Bergen, C. Niek van Dijk, Pim A. D. van Dijk, Francesca Vannini, Markus Walther, Martin Wiewiorski, Xiangyang Xu, Youichi Yasui, Ichiro Yoshimura, Alastair Younger, Zijun Zhang

Bibliographic record

VenueFoot & Ankle International · 2018
Typearticle
Languageen
FieldMedicine
TopicFoot and Ankle Surgery
Canadian institutionsQueen Elizabeth II Health Sciences CentreDalhousie University
Fundersnot available
KeywordsMedicineAnkleConsensus conferenceDelphi methodEvidence-based medicineStatement (logic)DelphiCartilagePathologyAlternative medicineLawPolitical scienceAnatomyArtificial intelligence

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 is to report the consensus statements on "Subchondral Pathology" 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 upon 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 9 statements on subchondral pathology reached consensus during the 2017 International Consensus Meeting on Cartilage Repair of the Ankle. No statements achieved unanimous support, but all statements reached strong consensus (greater than 75% agreement). All statements reached at least 81% agreement. CONCLUSIONS: This international consensus statements regarding subchondral pathology of the talus derived from leaders in the field will assist clinicians in the assessment and management of this difficult pathology.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.255
Threshold uncertainty score0.358

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.019
GPT teacher head0.266
Teacher spread0.247 · 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

Citations33
Published2018
Admission routes1
Has abstractyes

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