High Load With Lower Repetitions vs. Low Load With Higher Repetitions: The Impact on Asymmetry in Weight Distribution During Deadlifting
Bibliographic record
Abstract
This study investigated weight distribution between the lower limbs using a symmetry index (SI) score of the vertical ground reaction forces (GRF) and measures of postural stability in high load/low repetition (termed "heavy") and low load/high repetition (termed "light") deadlifting. Ten participants performed two deadlift protocols with equal cumulative external load. These protocols were designed to represent standard high load/low repetition and low load/high repetition workouts; order was random and separated by 7 days. An effect of lifting condition (p = .023) and set number (p = .011) was observed such that lifts in the heavy condition were less symmetrical than those in the light condition and lifts become more symmetrical as set number increased. There was no effect of lift number on symmetry of force production (p = .127). Additional analysis revealed that centre of pressure (COP) path length was greater during heavy lifts (p = .002) however COP range was unaffected suggesting controlled point of force application within the same boundaries regardless of lifting condition. As asymmetries have been previously associated with increased injury risk, greater training emphasis on the symmetrical performance of sub-maximal deadlifts should be considered to try to minimize the development of asymmetries.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".