Numerical breast models for commercial FDTD simulators
Bibliographic record
Abstract
Abstract—This paper presents the development of numerical human breast models suitable for commercial finite-difference time-domain (FDTD) simulators. The geometry of the breast models is derived from images obtained from Magnetic Resonance Imaging (MRI) scans. To avoid assigning tissue properties to every voxel, we apply the regression tree analysis to partition the breast tissue region into cuboid regions (cells) that exhibit similar pixel intensity (and hence have similar tissue structure). The local spatial averaging performed by the analysis addresses the MRI-inherent noise. Secondly, we use dielectric and Debye material to model the heterogeneity and dispersiveness of breast tissue. We find that Debye material offers higher attenuation in the high frequency region than dielectric material. We also confirm that assuming a fixed relaxation time constant in Debye material does not significantly affect the field. I.
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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".