Current Status and Emerging Techniques for Measuring the Dielectric Properties of Biological Tissues
Why this work is in the frame
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Bibliographic record
Abstract
Abstract The dielectric properties of biological tissues are key parameters that support the design and usability of a wide range of electromagnetic-based medical applications, including for diagnostics and therapeutics, and allow the determination of safety and health effects due to exposure to electromagnetic fields. While an extensive body of literature exists that reports on values of these properties for different tissue types under different measurement conditions, it is now evident that there are large uncertainties and inconsistencies between measurement reports. Due to varying measurement techniques, limited measurement validation strategies, and lack of metadata reporting and confounder control, reported dielectric properties suffer from a lack of repeatability and questionable accuracy. Recently, the American Society of Mechanical Engineers (ASME) Thermal Medicine Standards Committee was formed, which included a Tissue Properties working group. This effort aims to support the translation and commercialization of medical technologies, through the development of a standard lexicon and standard measurement protocols. In this work, we present initial results from the Electromagnetic Tissue Properties subgroup. Specifically, this paper reports a critical gap analysis facing the standardization pathway for the dielectric measurement of biological tissues. All established measurement techniques are examined and compared, and emerging ones are assessed. Perspectives on the importance and challenges in measurement validation, accuracy calculation, metadata collection, and reporting are also discussed.
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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 it