Center of Rotation and Hysteresis Quantification in the Wrist Utilizing Four-Dimensional Computed Tomography
Bibliographic record
Abstract
Abstract Wrist injuries limit function and can lead to long-term pain and disability. Current interventions aim to decrease pain and restore healthy function; however, healthy function during dynamic motion has not been fully characterized. Four-dimensional computed tomography (4DCT) can capture dynamic bony motion providing new insight to the dynamic wrist joint. Ten young healthy participants were scanned using a 4DCT scanner and three-dimensional (3D) models were made of the radius and carpal bones. Using helical axes and local coordinate systems for the radius, rotations of each bone were measured, and center of rotation was determined. In addition, hysteresis was quantified by measuring hysteresis area, the area between the curves of the forward and reverse motion of the wrist joint. The results showed that the wrist axis of rotation was located more proximal (−15.2 ± 1.3 mm distal) and dorsal (−0.8 ± 2.6 mm dorsal) in extension as compared with the flexion positions (−20.4 ± 1.6 mm distal; 3.9 ± 2.5 mm volar). In addition, no statistical differences were identified between the different directions of motion at each angle of wrist motion, with the exception of the trapezium at 30 degrees of extension. The largest hysteresis effect was noted in the trapezoid (112.8 deg2) and the smallest effect identified in the lunate (46.0 deg2). The results of this study may provide a better understanding of the dynamic nature of the wrist joint for identification of ligamentous injuries and replication of joint motion after surgical intervention.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".