Scapular kinematics and task specificity: The effect of load direction
Bibliographic record
Abstract
Our current understanding of healthy scapula motion is mainly based on studying the shoulder when it is generating an abduction torque against gravity. However, the shoulder can perform diverse tasks beyond abduction. In particular, little attention has been given to how scapula motion contributes to concentric adduction despite its involvement in high-demand tasks such as rock climbing and wheelchair transfers. Investigating scapular kinematics during concentrically loaded arm-lowering can provide insight into the mechanical demands underlying healthy scapula motion. In this study, we combined biplanar videoradiography and optical motion capture with a controllable cable machine to compare the three-dimensional humerothoracic, glenohumeral, and scapulothoracic kinematics between a weighted pull-down task (involving concentric shoulder adduction) and a weighted press-up task (involving concentric shoulder abduction) in ten healthy adults. We observed significantly more scapulothoracic upward rotation and less glenohumeral abduction during concentric adduction than concentric abduction. Our findings indicate that scapula upward rotation is not simply a function of overall humerothoracic elevation, but instead varies in a load-specific manner - potentially to orient the glenoid in a way that facilitates glenohumeral joint stability. We also observed substantial inter-individual variability in scapular kinematics within a task, and in how individuals responded to the different tasks. Our findings help provide a more well-rounded understanding of healthy scapular kinematics such that we can better identify and treat unhealthy motion (i.e., dyskinesis). Our findings can also inform musculoskeletal models that simulate scapulothoracic kinematics.
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".