Effect of the calculation methods on body moment of inertia estimations in individuals of different morphology
Bibliographic record
Abstract
Body segment moments of inertia (MOI) are estimated from data obtained from cadavers or living individuals. Though these methods can be valid for the general population, they usually are limited when applied to special populations (e.g., obese). The effect of two geometric methods, photogrammetry and two new methods, namely, inverse dynamics and angular momentum on the estimations of MOI in individuals of different body mass index (BMI) were compared to gain insight into their relative accuracy. The de Leva (1996) method was chosen as a criterion to determine how these methods behaved. MOI methods were not different in individuals with a normal BMI. On the average, MOI values obtained with inverse dynamics and angular momentum were respectively 13.2% lower for lean participants and 17.9% higher for obese subjects than those obtained from the de Leva method. The average Pearson coefficients of correlation between the MOI values, estimated by the de Leva method, and the other methods was 0.76 (+/-0.31). Since the proposed methods made no assumption on the mass distribution and segments' geometry, they appeared to be more sensitive to body morphology changes to estimate whole body MOI values in lean and obese subjects.
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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 | 0.001 | 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 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".