Three-dimensional hip and knee loading during the Copenhagen adductor exercise
Bibliographic record
Abstract
The Copenhagen adductor exercise (CAE) is used for groin muscle strengthening. While these muscles primarily act in the frontal plane, the hip adductor muscles may also act in the sagittal and transverse planes. Therefore, the CAE likely imposes three-dimensional (3D) muscular demands at both the hip and knee. This study aimed to quantify the 3D hip and knee joint loading during variations of the CAE. Eleven men and 13 women performed the exercise with the support stand at the knee, ankle, and midway between the knee and ankle. Ground reaction forces under the stand and reflective markers trajectories were recorded to calculate hip and knee net joint moments (NJM). Hip adductor NJM was largest for the ankle support (1.54 ± 0.23 Nm·kg −1 ) and smallest for the knee support (0.93 ± 0.16 Nm·kg −1 ; P < 0.001). Most participants had a hip extensor NJM, that was also greater for more distal support locations (Δ ankle-mid = −0.10 ± 0.21 Nm·kg −1 ; Δ ankle-knee = − 0.20 ± 0.27 Nm·kg −1 ; P < 0.001). Support locations distal to the knee had knee adductor and flexor NJM. The hip and knee sagittal plane NJMs were strongly correlated with transverse plane thigh ( r = 0.97–0.98, P < 0.017) and shank ( r = 0.89–0.93, P < 0.017) orientations, respectively. Medial thigh rotation was associated with a hip flexor NJM while lateral thigh rotation was associated with a hip extensor NJM. CAE requires frontal and sagittal plane muscle efforts at the hip and knee, which are greater for more distal support locations.
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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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".