Morphological Study on Human Body Absorption Cross Section in a Reverberation Chamber From 1 GHz to 16 GHz
Bibliographic record
Abstract
The human body absorption cross section (ACS) is important in nonionizing radiation dosimetry, but it is always hard to accurately evaluate the ACS of an individual from his or her morphological parameters, such as height and weight. To obtain an empirical formula that can evaluate the ACS from morphological parameters, 48 subjects with different morphological parameters were measured from 1 to 16 GHz in a reverberation chamber. The ACS was extracted from the power delay profile. This has the advantage of not requiring antenna radiation efficiency, and it has not been previously used in a wideband group study like this. The accuracy of the ACS measurement is demonstrated by comparison with the ACS of a spherical model with known structure and material, and the mean absolute percentage error of the sphere measurement is just 3.4%. Statistical analysis shows that the body surface area (BSA) has the strongest correlation with the ACS among all the morphological parameters; therefore, we present a new empirical ACS formula as a function of BSA and frequency. This will be of interest to those considering dosimetry, and in computing the effect of human body absorption on radio propagation in vehicles and other structures.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".