Variability of Lifting Technique of Experienced Women Lifters across Light, Medium and Heavy Loads
Bibliographic record
Abstract
The purpose of this study was to examine the variability in lifting technique kinematics within and between 35 female subjects when lifting light, medium and heavy loads. Each female performed five lifts in a free-style from floor to shoulder-height of a box (37times;29times;27 cm) with handles at three weights: 5, 10 and 15 kg. Polhemus Fastrak™, 3D electromagnetic sensors placed on the wrist, T***I, L***I and S***I spinous processes revealed spinal kinematics that showed increasing variability with heavier loads at the T***I sensor, L***I sensor, thoracic flexion angle, lumbar flexion angle and trunk flexion displacements. The velocity profiles provided similar results of variability for the T***I sensor, L***I sensor, S***I sensor, thoracic and lumbar flexion velocities. In addition, differences in technique were examined between loads using knee bend, box to body distance and trunk mean angles.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| 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) | 0.001 | 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".