Upper limb and trunk kinematics in tree planters during three load carriage conditions
Bibliographic record
Abstract
Tree planters use various strategies to unload the seedlings from their bags. This study examines differences in upper limb and trunk joint angles during three load carriage conditions: (1) load evenly distributed to the right and left sides of the body – evenly loaded (2) load entirely on the right side – right loaded and (3) load entirely on the left side – left loaded. Data were collected in the field in Northern Ontario. Inertial motion sensors were placed on the right hand, right and left forearms and upper arms, sacrum, and T1 vertebrae. Using relative sensor orientation, joint angles were determined for the right wrist, right and left elbow and the trunk for the three load carriage conditions during normal planting tasks. The main findings were: 1) In the left loaded condition, the right wrist was less extended, the right elbow was more flexed, the trunk experienced less right-rotation, and the right and left forearms were less pronated than in either the evenly loaded or right loaded conditions. 2) In both the left and right loaded conditions, the left forearm was less pronated, and the trunk was less flexed than in the evenly loaded condition. Results suggest that asymmetrical tree load carriage results in more neutral postures than symmetrical tree load carriage.
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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 | 0.000 |
| 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) | 0.002 | 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".