Knowledge of Repetition Range Does Not Affect Maximal Force Production Strategies of Adolescent Females
Bibliographic record
Abstract
PURPOSE: Contrary to adult force reserve strategies, it is not known whether adolescent females with less experience performing maximal voluntary contractions (MVC) have specific responses to a known or unknown fatigue endpoint. METHODS: Using a counterbalanced random crossover design, fourteen inexperienced female adolescents completed three elbow flexor (EF) fatiguing protocols. Participants were randomly assigned to a control (informed they would perform 12 MVCs), unknown (not informed of the number of MVCs to be completed, but stopped after 12) or deception condition (instructed to complete 6 MVCs, however, after the 6th repetition performed another 6 MVCs). Before and during the interventions, EF impulse, force, and biceps brachii (BB) and triceps brachii (TB) electromyography (EMG) activity were recorded. RESULTS: Participants exhibited decreases in impulse (10.9%; p<0.05), force (7.5%; p=0.001), BB (16.2%; p<0.05) and TB (12.9%; p<0.05) EMG activity between the pre-test and the first repetition of all protocols. Knowledge of endpoint, or lack of it, did not change measures with the repeated MVCs. When informed about the final repetition, force remained depressed suggesting no physiological reserve. CONCLUSION: Adolescent females exhibited an anticipatory response to the task of performing repeated MVCs. A lack of change with knowledge of endpoint indicates that those lacking in MVC experience do not employ the same pacing strategies as in previous studies of participants with MVC experience.
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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) | 0.003 | 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".