Correlation of Patellar Tracking Pattern With Trochlear and Retropatellar Surface Topographies
Bibliographic record
Abstract
The study was aimed to test the hypothesis that in the knee extension range 100 to 30 deg, the patellar "out-of-plane" tracking pattern is controlled by the passive restraint provided by the topographic interaction of the patellofemoral contacting surfaces. The out-of-plane tracking pattern, i.e., the pattern of patellar displacements not in the plane of knee extension/flexion, consists of translation in the medial-lateral direction, and rotations about the anterior-posterior axis (spin) and the proximal-distal axis (tilt). Using 15 fresh-frozen knees subjected to extensor moment magnitudes comparable to those in the "static-lifting" activity (foot-ground reaction = 334 N), the patellar displacements were measured using a calibrated six-degree-of-freedom electromechanical goniometer. The topographies of the trochlear and retropatellar surfaces were then measured using a calibrated traveling dial-gage arrangement and the same coordinate system used for the displacement measurements. Three indices were defined to quantify particular natural features of the three-dimensional topographies that are expected to control the patellar displacements. Correlation of the indices with their corresponding displacements showed that topographic interaction was significant in the control of all three displacements. However, for patellar spin, unlike for the other two displacements, the direction of the active quadriceps tension vector was also a significant controlling factor. Patellar medial-lateral translation was found to be controlled dominantly by the trochlear topography, while retropatellar topography also had a significant role in the control of the other two displacements.
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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 | 0.000 | 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 | 0.000 |
| 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".