Biomechanical Evaluation of Carpal Kinematics during Simulated Wrist Motion
Bibliographic record
Abstract
<b>Background</b> Flexion and extension of the wrist is achieved primarily at the radiocarpal and midcarpal joints. Carpal kinematics have been investigated, although there remains no consensus regarding the relative contribution of each bone to wrist motion. <b>Purpose</b> To determine the kinematics of the scaphoid, lunate, and capitate during unconstrained simulated wrist flexion/extension and to examine the effect of motion direction on the contribution of each bone. <b>Materials and Methods</b> Seven cadaveric upper extremities were tested in a passive wrist simulator with 10N tone loads applied to the wrist flexors/extensors. Scaphoid, lunate, and capitate kinematics were captured using optical tracking and analyzed with respect to the radius. <b>Results</b> Scaphoid and lunate motion correlated linearly with wrist motion (<i>R</i> <sup>2</sup> = 0.99, 0.97). In extension, the scaphoid and lunate extended 83 ± 19% and 37 ± 18% relative to total wrist extension (<i>p</i> = 0.03, 0.001), respectively. In flexion, the scaphoid and lunate flexed 95 ± 20% and 70 ± 12% relative to total wrist flexion (<i>p</i> = 1.0,0.01) , respectively. The lunate rotated 46 ± 25% less than the capitate and 35 ± 31% less than the scaphoid. The intercarpal motion between the scaphoid and lunate was 25 ± 17% of wrist flexion. <b>Conclusion</b> The scaphoid, lunate, and capitate move synergistically throughout planar wrist motion. The scaphoid and lunate contributed at a greater degree during flexion, suggesting that the radiocarpal joint plays a more critical role in wrist flexion. <b>Clinical Relevance</b> The large magnitude of differential rotation between the scaphoid and lunate may be responsible for the high incidence of scapholunate ligament injuries. An understanding of normal carpal kinematics may assist in positioning carpal bones during partial wrist fusions and in developing more durable wrist arthroplasty designs.
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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 | 0.005 | 0.004 |
| 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".