An investigation of 2 techniques for optimizing joint surface congruency using multiple cylindrical osteochondral autografts
Bibliographic record
Abstract
PURPOSE: To compare 2 techniques for optimizing joint congruency for miniature osteochondral autografting in the knee: intrinsic postoperative forces acting on overdrilled autografts protruding from the femur versus alignment by a surgeon at the time of grafting. TYPE OF STUDY: Controlled animal model experiment. METHODS: A full-thickness cartilage defect was created on the weight-bearing surface of the medial femoral condyle of 13 mature sheep. Three 4.5 x 10 mm cylindrical autografts were inserted into 14-mm deep recipient holes such that the grafts were held in place by side-wall friction alone. One treatment group received grafts that were delivered flush with the surrounding cartilage and the second group received grafts that were left 2-mm proud of the joint surface. RESULTS: Three months postoperatively, the proud grafts had been repositioned by weight bearing but perigraft fissuring and fibroplasia, and subchondral cavitations were serious complications. It is suspected that these complications were caused by excessive motion between the graft and recipient site in the proud grafts. CONCLUSIONS: Grafts should be delivered flush with the joint surface when performing osteochondral transfers to avoid graft micromotion and the consequent interference with graft integration and function.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".