Accuracy of the Borg CR10 Scale for Estimating Grip Forces Associated with Hand Tool Tasks
Bibliographic record
Abstract
The gripping of tools is required by many industrial operations, and an important aspect of exposure assessment is determining the grip force output of operators. Ratings of perceived exertion can provide an indirect measure of grip force; however, reports in the literature of the use of Borg CR10 scale ratings as a surrogate measure of grip force have been mixed. During a laboratory study with 16 participants, power grip forces were measured directly during three hand tool task simulations: (1) a screwdriver task, (2) a ratchet task, and (3) a lift and carry task, each performed at four force/load levels. Borg scale ratings reported following each trial were compared with mean, peak, and integrated grip forces for the respective trials. Pearson correlations conducted on an individual basis were greatest for the screwdriver task, r approximately 0.9. Correlations for integrated grip force were generally better than for mean or peak force. Correlations were also performed on data pooled for all participants, simulating a cross-sectional sampling approach. Correlations made with pooled data were weaker than when conducted on an individual basis, ranging from r = 0.26 for peak grip force for the lift and carry task, to r = 0.79 for the screwdriver task. When the pooled data were normalized to individual maximum voluntary grip exertions, correlation generally improved but not to the level of the "individually scaled" data. Based on these findings, a protocol is proposed that could improve the strength of correlations between direct measures of grip force and ratings of perceived exertion. Differences in strength of correlation between task simulations are discussed with respect to differences observed in force distributions about the handle for the three tasks.
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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".