A biomechanical assessment of the coupling of torsion and tension in the human scapholunate ligament
Bibliographic record
Abstract
The mechanical behaviour of human scapholunate ligaments is not well described in the literature with regard to torsion. In this study, intact scapholunate specimens were mechanically tested in torsion to determine whether a simultaneous tensile load was generated. Human intact scapholunate specimens (n = 19) were harvested. The scaphoid and lunate bones were potted in square chambers using epoxy cement, while the interposing ligament remained exposed. Each specimen was mounted rigidly in a specially designed test jig and remained at a fixed axial length during all tests. Specimens were subjected to a torsional load regime that included cyclic preconditioning, ramp-up, stress relaxation, ramp-down, rest, and torsion to failure. Torque and axial tension were monitored simultaneously. The relationship between torsion and tension was determined. Graphs of torque versus tension were generated, from which outcome measures were extracted. Tests demonstrated a clear relationship between applied torsion and the resulting generation of tension for the ligament during ramp-up (torsion-to-tension ratio, 38.86 +/- 29.00 mm; linearity coefficient R2 = 0.89 +/- 0.15; n = 19), stress relaxation (torsion-to-tension ratio, 23.43 +/- 15.84 mm; R2 = 0.90 +/- 0.09; n = 16), and failure tests (torsion-to-tension ratio, 38.81 +/- 26.39mm; R2 = 0.77 +/- 0.20; n = 16). No statistically significant differences were detected between the torsion-to-tension ratios (p = 0.13) or between the linearity (R2) of the best-fit lines (p > 0.085). A strongly coupled linear relationship between torsion and tension for the scapholunate ligament was exhibited in all test phases. This may suggest interplay between these two parameters in the stabilization of the ligament during normal motion and for injury cascades.
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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 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".