Detection at microwave frequencies based on self-adjoint sensitivity analysis
Bibliographic record
Abstract
A novel general formulation of the response sensitivity analysis is proposed and implemented in a computationally efficient algorithm for the detection of electrically small scatterers in a known background medium. The responses of the background medium where no scatterers are present are modeled via ultra-wideband time-domain simulation. Using these modeled responses and the measured responses of the examined object, 3D derivative maps are obtained within the object's volume. The minima or maxima in these maps indicate the locations where the voxel permittivities and conductivities differ significantly between the measured and modeled media. Localization of the scatterers in a complex heterogeneous example is successfully conducted. The limitations of the detection algorithm and its resolution are studied using a homogeneous background example in terms of the number of transmission/reception points, the dielectric contrast and the size of the scatterer.
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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 | 0.001 | 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 | 0.001 |
| 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".