Superlens Enhanced 2-D Microwave Tomography With Contrast Source Inversion Method
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Bibliographic record
Abstract
The contrast source inversion (CSI) algorithm is one of the primary techniques used for solution of non-linear inverse problems in microwave tomography. In this paper, we describe a modification of the CSI method adapted to imaging of the 2-D objects in the presence of the focusing media under TM-polarization. The focusing media is presented in the form of the Veselago lens. The data domain and imaging domain are properly positioned with respect to the location of the lens. Specifically, the sensors are located at the focal points of the lens with respect to the location of the individual pixels discretizing the contrast source. Such positioning of the source and observation locations in the presence of the lens, eliminates rank deficiency in the formulation of the inverse problem and results in significant improvements to both convergence speed of underlying conjugate gradient iterations and the accuracy of the image reconstruction in the CSI method.
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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 | 0.000 | 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 it