Effects of Ventilation on Segmental Bioimpedance Spectroscopy Measures Using Generalizability Theory
Bibliographic record
Abstract
The purpose of this study was to examine the effect of three ventilation conditions (i.e., normal, regimented, and no-ventilation) on the reproducibility of bioimpedance scores in humans for the forearm and trunk segments. One hundred able-bodied North American men and women, from 18 to 71 years of age, volunteered as participants. The experimenters used a Xitron Bio-Impedance Analyzer System model 4200 instrument with Hydra software (Xitron Technologies, San Diego, California, USA) to collect bioimpedance data on extracellular fluid and intracellular fluid scores. The experimenters analyzed the data using the generalizability theory,with persons as the facet of differentiation and time as the facet of generalization. The major findings were (a) ventilation conditions did not have a significant impact on the reproducibility of the test scores, (b) the forearm segment produced consistently higher intracellular fluid generalizability coefficients across three ventilation conditions for both gender groups when compared to the trunk segment, (c) the trunk segment produced intracellular fluid generalizability coefficients that were higher for the male group, and (d) the measurement error affected extracellular fluid scores less than segmental intracellular fluid scores.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.018 | 0.105 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), 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".