Isometric Pull and Push Strengths of Paraplegics in the Workspace: 2. Statistical Analysis of Spatial Factors
Bibliographic record
Abstract
The effect of reach levels, horizontal angles, and vertical angles on isometric pull and push strengths of male and female was determined. Highly significant increases in men's push strength were found between extreme to maximum reaches, and from extreme to normal reaches. However, for women's push strength, a significant increase was found only between extreme to maximum reach. Significant or highly significant increases were found in men's and women's pull strength between the horizontal angle (theta) sagittal through the active shoulder (90 degrees ) and other angles (0, 45, and 135 degrees ). However, for men's push strength, highly significant increases were found between the horizontal angle 45 degrees from the frontal plane, and other angles. For women's push strength, significant or highly significant increases were found between the horizontal angles 0 degrees and angles of 90 and 135 degrees. For men's and women's pull strength, significant or highly significant increases were found between the vertical angle (phi), 90 degrees, and other angles (-20, 0, and 45 degrees ). Similar increases were found for women's push strength between the 45 degrees angle and other angles. In the design of a workstation for paraplegics that requires pull and push forces, consideration must be given to the spatial factors.
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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 | 0.004 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".