A biomechanical study of clamping technique on patellar tendon surface strain and material properties using digital image correlation
Bibliographic record
Abstract
Several clamping techniques exist for ex vivo mechanical testing of tendon. For the patellar tendon, one can choose to clamp directly to the bony attachment sites, the tendon itself, or a combination of the two; however, the influence of these techniques on localized strains and gross material properties is unknown. To this end, uniaxial tensile tests were performed on eleven porcine patellar tendons in three clamping setups while digital image correlation was used to measure axial and transverse strains, Young's modulus, and Poisson's ratio. The setups involved clamping to: 1) the patella and tibia, 2) the patella and the dissected distal tendon, and 3) the dissected proximal and distal tendon. Axial strains in the tendon-tendon clamping setup were 181% higher than patella-tibia clamping (p = 0.002) and 131% higher than patella-tendon clamping (p = 0.006). Transverse strains were not significantly different between clamping conditions (p ≥ 0.118). Young's modulus was 50% (p < 0.001) greater for patella-tibia clamping and 42% (p < 0.001) greater for patella-tendon clamping when compared to tendon-tendon clamping. For all clamping setups, the tendon illustrated auxetic behaviour (i.e., negative Poisson's ratio); however, the Poisson's ratios were 80% smaller in the patella-tibia setup (p = 0.006) and 71% smaller patella-tendon setup (p = 0.007) compared to the tendon-tendon setup. These results illustrate that discretion should be utilized when reporting material properties derived from mechanical tests involving direct clamping to the dissected patellar tendon at both ends, as this clamping technique significantly increases axial strains, reduces Young's modulus, and alters the tendon's natural auxetic behaviour.
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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 | 0.000 | 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) | 0.002 | 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".