Evaluation of body composition by two current bioelectric impedance small scales as compared with two new anthropometric equations and the two most published used equations used as references (1031.12)
Bibliographic record
Abstract
Assessment of adipose tissue and lean body mass (LBM) is useful in clinics to follow‐up obese patients on diet and cases of body weight (BW) loss (e.g. malnutrition) or gain of muscle mass due to physical training or experimental special diets or products. The present study was conducted on 76 well‐selected healthy Caucasian women aged 22.0 ± 1.9 yrs. BW and body fat distribution were normal based on BMI and Waist/Hip ratio. Body frame was medium based on ∑acromial‐bitronchanteric distances. Circumferences and skinfolds were measured at several Lohman sites; muscular circumferences and surfaces were calculated by means of validated equations. % adipose tissue values obtained from Tanita and the practical Gallagher et al.’s equation based on BMI were similar to the Durnin & Womersly’s reference equation; Omron over‐estimated by 22.8% (( p <0.0001). The Tanita scale is misleading for LBM; the value 76.9 ± 7.7% of BW corresponds to total fat‐free body (FFB), a body compartment of no great clinical interest. Values from Lee et al.’s equation and the Omron scale reflected LBM. Compared with the value derived from Heymsfield et al.’s reference equation for muscular tissue, the difference was significant ( p <0.001) in the former case; the % ∆ of Omron was only ‐0.5. In conclusion, the two BEI scales are not equal in determining BC, Tanita and Omron being reliable only for adipose or muscular tissues, respectively.
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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 | 0.006 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".