Revision and Salvage Management: Proceedings of the International Consensus Meeting on Cartilage Repair of the Ankle
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.155 | 0.148 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.008 | 0.004 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.005 | 0.009 |
| Research integrity | 0.006 | 0.009 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".