Load balance in total knee arthroplasty: an <i>in vitro</i> analysis
Bibliographic record
Abstract
BACKGROUND: One of the goals of total knee arthroplasty (TKA) is to balance the loads between the compartments of the knee. An instrumented load cell that measures compartment loads in real time is utilized to evaluate conventional, qualitative methods of achieving this balance. METHODS: TKA was performed on 10 cadaveric knees. Prior to and after load balancing, compartment forces were measured at flexion angles of 0-90 degrees. Knees were randomly assigned into one of two groups, based upon whether or not the surgeons could visualize the load cell's output during balancing. RESULTS: Prior to attempting load balance, there were significant differences between the medial and lateral compartment loads for all knees (p < 0.05). After attempting balance with the aid of the load cell, there was equal load balance at all angles studied. Without the aid of the load cell, balance was not consistently achieved at every angle. CONCLUSIONS: Conventional load balancing techniques in TKA are not perfect.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".