Determining <i>in vivo</i> sternoclavicular, acromioclavicular and glenohumeral joint centre locations from skin markers, CT-scans and intracortical pins: A comparison study
Why this work is in the frame
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Bibliographic record
Abstract
To describe shoulder motion the sternoclavicular, acromioclavicular and glenohumeral joint centres must be accurately located. Within the literature various methods to estimate joint centres of rotation location are proposed, with no agreement of the method best suited to the shoulder. The objective of this study was to determine the most reliable non-invasive method for locating joint centre locations of the shoulder complex. Functional methods using pin mounted markers were compared to anatomical methods, functional methods using skin mounted markers, imaging-based methods using CT-scan data, and regression equations. Three participants took part in the study, that involved insertion of intracortical pins into the clavicle, scapula and humerus, a CT-scan of the shoulder, and finally data collection using a motion analysis system. The various methods to estimate joint centre location did not all agree, however suggestions about the most reliable non-invasive methods could be made. For the sternoclavicular joint, the authors suggest the anatomical method using the most ventral landmark on the sternoclavicular joint, as recommended by the International Society of Biomechanics. For the acromioclavicular joint, the authors suggest the anatomical method using the landmark defined as the most dorsal point on the acromioclavicular joint, as proposed by van der Helm. For the glenohumeral joint, the simple regression equation of Rab is recommended.
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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) | 0.001 | 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 it