Effect of sagittal plane mechanics on ACL strain during jump landing
Bibliographic record
Abstract
The relationships between non-contact anterior cruciate ligament injuries and the underlying biomechanics are still unclear, despite large quantities of academic research. The purpose of this research was to study anterior cruciate ligament strain during jump landing by investigating its correlation with sagittal plane kinetic/kinematic parameters and by creating an empirical model to estimate the maximum strain. Whole-body kinematics and ground reaction forces were measured from seven subjects performing single leg jump landing and were used to drive a musculoskeletal model that estimated lower limb muscle forces. These muscle forces and kinematics were then applied on five instrumented cadaver knees using a dynamic knee simulator system. Correlation analysis revealed that higher ground reaction force, lower hip flexion angle and higher hip extension moment among others were correlated with higher peak strain (p < 0.05). Multivariate regression analyses revealed that intrinsic anatomic factors account for most of the variance in strain. Among the extrinsic variables, hip and trunk flexion angles significantly contributed to the strain. The empirical relationship developed in this study could be used to predict the relative strain between jumps of a participant and may be beneficial in developing training programs designed to reduce an athlete's risk of injury. © 2016 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 34:1636-1644, 2016.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".