Outside‐In Single–Lasso Loop Technique for Meniscal Repair: Fast, Economic, and Reproducible
Bibliographic record
Abstract
The current understanding of the biomechanical role of the meniscus, in conjunction with the increasing efforts to achieve its preservation within the orthopaedic community during treatment of meniscal lesions, has prompted the development of different meniscal repair techniques. The outside-in technique is recommended for anterior horn and middle-segment meniscal tears and has been recognized as a low-cost procedure with a low incidence of complications. Diverse modifications of this technique have been published over the past decade. On the basis of these previous outside-in technique modifications and aiming to simplify and reduce the number of surgical steps, as well as simplify suture and/or instrument manipulation, during this technique, we describe the single-lasso loop outside-in technique for meniscal repair. We believe this modified technique represents a simplified, economic, and highly reproducible procedure option whenever an outside-in technique for meniscal repair is considered.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".