Normalization of Ground Reaction Forces, Joint Moments, and Free Moments in Human Locomotion
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
Authors who report ground reaction force (GRF), free moment (FM), and resultant joint moments usually normalize these variables by division normalization. Normalization parameters include body weight (BW), body weight x height (BWH), and body weight x leg length (BWL). The purpose of this study was to explore the appropriateness of division normalization, power curve normalization, and offset normalization on peak GRF, FM, and resultant joint moments. Kinematic and kinetic data were collected on 98 subjects who walked at 1.2 and 1.8 m/s and ran at 3.4 and 4.0 m/s. Linear curves were best fit to the data, and regression analyses performed to test the significance of the correlations. It was found that the relationship between peak force and BW, as well as joint moments and BW, BWH, and BWL, were not always linear. After division normalization, significant correlations were still found. Power curve and offset normalization, however, were effective at normalizing all variables; therefore, when attempting to normalize GRF and joint moments, perhaps nonlinear or offset methods should be implemented.
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.
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 | 0.001 | 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 it