Three-dimensional continuous muscle moment arm maps for the anatomical shoulder
Bibliographic record
Abstract
A muscle's moment arm represents its mechanical advantage and indicates its role in joint actuation and rotational stability. The objective of this study was to use an ex-vivo simulator to map the moment arms of eight major shoulder muscles across a continuous range of motion. The three-dimensional moment arms for the deltoid (anterior, lateral, and posterior), subscapularis (inferior and superior), supraspinatus, infraspinatus, and teres minor were measured in eight specimens (57 ± 6 years) using the tendon excursion method. The anterior deltoid had a significantly larger elevation moment arm in anterior planes of elevation (p < 0.001) while the lateral deltoid had a significantly larger elevation moment arm in posterior planes (p < 0.001). The posterior deltoid was an antagonist to elevation with anterior arm orientations (p < 0.001). The supraspinatus had biphasic function; in anterior elevation planes it was a horizontal extensor and internal rotator but was a horizontal flexor and external rotator in posterior planes (p < 0.001). The infraspinatus and superior subscapularis were both arm elevators, but the infraspinatus was an external rotator and horizontal extensor while the superior subscapularis was an internal rotator and horizontal flexor. The inferior subscapularis was a horizontal flexor and internal rotator while the teres minor was an antagonist to elevation, horizontal extensor, and external rotator. Each muscle had a multifaceted function which changed significantly with arm orientation for all muscles except the inferior subscapularis. The muscle moment arms maps created in this study improve current understandings of the three-dimensional function of eight major muscles in the shoulder.
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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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".