Human muscle strength definitions, measurement, and usage: Part I – Guidelines for the practitioner1 1The recommendations provided in this guide are based on numerous published and unpublished scientific studies and are intended to enhance worker safety and productivity. These recommendations are neither intended to replace existing standards, if any, nor should be treated as standards. Furthermore, this document should not be construed to represent institutional policy.The following individuals participated in the discussion of the earlier version of this guide. Their suggestions (written or verbal) were incorporated by the authors in this version: A. Aaras, Norway; J.E. Fernandez, U.S.A.; A. Freivalds, U.S.A.; T. Gallewey, Ireland; M. Jager, Germany; S. Konz, U.S.A.; H. Krueger, Switzerland; K. Landau, Germany; A. Luttmann, Germany; J.D. Ramsey, U.S.A.; M-J. Wang, Taiwan.
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.
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 | 0.013 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it