A New Method for Noninvasive Measurement of Multilayer Tissue Conductivity and Structure Using Divided Electrodes
Bibliographic record
Abstract
This paper outlines a new method for measuring multilayer tissue conductivity and structure by using divided electrodes, in which current electrodes are divided into several parts. Our purpose is to estimate the multilayer tissue structure and the conductivity distribution in a cross section of the local tissue by using bioresistance data measured noninvasively. The effect of the new method is assessed by computer simulations using a typical two-dimensional (2-D) model. In this paper, the conductivity distribution in the model is analyzed based on a finite difference method (FDM) and a steepest descent method (SDM). Simulation results show that the conductivity values of skin, fat, and muscle layers can be estimated with an error of less than 0.1%. When random noise at various levels is added to the measured resistance values, estimates of the conductivity values for skin, fat, and muscle layers are still reasonably precise: their root mean square errors are about 1.06%, 1.39%, and 1.61% for 10% noise. In a 2-D model, increasing the number of divided electrodes permits simultaneous estimates of tissue structure and conductivity distribution. Optimal configuration for divided electrodes is examined in terms of dividing pattern.
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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 | 0.000 | 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".