Exploring the Influence of Strength and Load on Back Squat Kinematics During Sets to Volitional Failure
Bibliographic record
Abstract
Varsity athletes often train and compete in high fatigued states. Under those conditions, their movement could be affected. With continuous exposure to a different movement pattern due to fatigue, athletes could ingrain movement patterns that are undesirable for performance or risk of injuries. The purpose of this thesis was to assess: 1) change in lower extremities joint kinematics within a set to volitional failure, 2) the influence of strength and load on the magnitude of change in joint kinematics. Dependent measures included change in peak ankle dorsiflexion angle, knee flexion angle, hip flexion angle, and trunk flexion angle while the independent measures were the load (55% 3RM versus 85% 3RM), 3RM and time (onset and end of each set). It is hypothesized that athletes with a greater 3RM will demonstrate the greatest change in movement, especially in the low load condition.
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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".