Differentiation of strains in the lateral and medial bands of the iliofemoral ligament: A segmental approach
Bibliographic record
Abstract
Iliofemoral ligament strains have been assessed in a circumscribed portion, limiting the information regarding the strains in the proximal, mid and distal portions. The purpose of this study is to describe the longitudinal and transversal strain within the proximal, mid and distal portions of the lateral and medial bands of the iliofemoral ligament. Ten fresh cadaveric specimens were assessed. The iliofemoral ligaments were divided into medial and lateral bands. Hemispherical beads (2.6 mm) were placed on the lateral and medial borders of each band. Four positions were assessed: abduction, extension, internal and external rotations combined with extension. The hemispherical beads were scanned at the end range of motion using a laser scanner. The three-dimensional position of each bead was used to estimate longitudinal and transversal strains. A three-factor ANOVA was used to compare movements, borders, and portions within each ligament for longitudinal strains. A one-way ANOVA was used to compare transversal strains between portions. This technique showed mean reliability (ICC: 2, 1) of 0.90 ± 0.06. The external rotation showed the highest strains in both ligaments (p < 0.05). Abduction showed a significant difference between the lateral and medial borders in both bands (p = 0.001). Eight movement-border combinations showed a significant difference between proximal, medial, and lateral portions (p < 0.005). According to our results, there is a clear effect of portions (proximal, mid and distal) within the ligament and movements. Abduction shows the lowest strains longitudinally but the largest strains transversally. Although we do not know the impact of this phenomenon, future studies should assess the strains following hip arthroscopies. The latter might improve the impact of this procedure on hip biomechanics. Lastly, the iliofemoral ligament should be assessed using a segmental approach rather than as a complete unit.
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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 | 0.000 | 0.000 |
| 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) | 0.000 | 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".