A Novel Application of the Principles of Linear Elastic Fracture Mechanics (LEFM) to the Fatigue Behavior of Tendon Tissue
Bibliographic record
Abstract
BACKGROUND: Experiments on the fatigue of tendons have shown that cyclic loading induces failure at stresses lower than the ultimate tensile strength (UTS) of the tendons. The number of cycles to failure (Nf) has been shown to be dependent upon the magnitude of the applied cyclic stress. METHOD OF APPROACH: Utilizing data collected by Schechtman (1995), we demonstrate that the principles of Linear Elastic Fracture Mechanics (LEFM) can be used to predict the fatigue behavior of tendons under cyclic loading for maximum stress levels that are higher than 10% of the ultimate tensile strength (UTS) of the tendon (the experimental results at 10% UTS did not fit with our equations). CONCLUSIONS: LEFM and other FM approaches may prove to be very valuable in advancing our understanding of damage accumulation in soft connective tissues.
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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) | 0.001 | 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 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".