Application of robotic technology in biomechanics to study joint laxity
Bibliographic record
Abstract
PRIMARY OBJECTIVE: To evaluate whether in vitro joint testing using a robot with six degrees of freedom is useful for evaluating changes in joint laxity as a result of chronic osteoarthritis (OA). RESEARCH DESIGN: Repeated measures. METHODS: Broyden's method of solving nonlinear systems of equations drove a hybrid method of load and position robotic control. Sheep stifles (knee joints) were loaded between 3 Nm of internal load through to 3 Nm of external load in 1 Nm increments. Kinematic and morphologic data from five healthy ovine stifles were compared to the chronic OA effects in four surgically destabilized stifles. RESULTS: Stifles with chronic OA showed increases in stiffness while range of motion decreased. Gross morphologic changes included osteophytes and cartilage fibrillation. DISCUSSION: Robotic testing proved useful for evaluating changes in joint mechanics as a result of chronic OA. We observed morphological changes and associated increases in joint stiffness and decreased laxity.
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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) | 0.000 | 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 | 0.000 |
| 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".