Borg’s scales in strength training; from theory to practice in young and older adults
Bibliographic record
Abstract
This study is the first to apply Borg's psychophysical equation to measuring responses to strength training with weights machines. Theoretical constructs of Borg's scales were assessed in younger and older adults to estimate the appropriate load and number of repetitions required to meet recommended practice guidelines. A younger group (YG; 20 males, 20 females; aged 19-38 years) and older group (OG; 13 males, 13 females; aged 50-75 years) participated in 3 experiments. Experiment 1: YG performed 2-repetitions of incremented loads during triceps-elbow extensions and knee extensions to level 7 on Borg's CR10 Scale. Experiment 2: YG (n = 16) then performed 12-repetitions at the loads from experiment 1 that elicited CR10 ratings 1.5, 3.0, and 5.0. Experiment 3: OG performed 15-repetitions of "lat-pull" and leg press at 15-repetition maximum (RM) load. In experiments 2 and 3, CR10 or Borg RPE were measured every 2 repetitions. Experiment 1 revealed classic psychophysical response growth exponents between 1.1 and 1.8, which were greater in arms than legs (p < 0.001) and in females (p < 0.001). Theoretical estimates of 1RM were derived from the growth curves for the weights eliciting CR10 ratings of 1.5, 3, and 5. CR10 ratings of 3 to 6 fell within estimates of 40%-70% 1RM. Experiments 2 and 3 revealed, for constant load exercise "over time" (12 and 15 repetitions) from an initial CR10 rating of 4 to 6, a linear increase of 1 scale point for every 3 to 4 repetitions. In conclusion, Borg's equation has been used to set theoretical estimates of a %1RM. Relevant to current practice guidelines was the ability to set appropriate loads in relation to performing recommended numbers of repetitions (e.g., if the CR10 rating is >6 after 2 repetitions, the weight is likely be too heavy to complete 12 to 15 repetitions).
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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 | 0.009 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".