Bibliographic record
Abstract
Although the human hip is commonly thought to be a ball-and-socket \njoint, recent 3D studies suggest that the hip translates as well as \nrotates. This is of interest not only for biomechanics but also \nclinically, because hip translation may be important to physiotherapy \nand to computer-assisted surgery for total hip replacement. Previous \n3D studies have evaluated hip kinematics as well as morphology by CT, \nMRI and surgical intervention. A minimally invasive, inexpensive, and \naccurate way of measuring hip shape and motion may be useful in basic \nscience and clinical application. This work used prototype software \nto quantify planar hip morphology and kinematics from plain 2D \nradiographs. \n \nEllipses were fit to the articular contours of the femoral head and \nacetabulum of plain 2D radiographs of arthritic and dysplastic \npatients. The prototype software was validated in a study performed \nby three board-certified orthopedic surgeons. It was found to be \nefficient and reliable, taking less than one minute to quantify planar \nhip morphology and having no statistical difference between the \nobservers. \n \nThe prototype software was used in a clinical study to quantify planar \nhip kinematics. Preoperative AP pelvic radiographs were taken of 11 \nTHA patients in 4 different positions. The semi-automated fits \ndetected a mean femoral head translation of 3.42mm, with no \ndiscernible directional pattern. Every one of these arthritic \npatients exhibited substantial planar hip translation. \n \nThe findings are consistent with the hypothesis that hip morphology \nand kinematics can be quantified from plain 2D radiographs.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".