On the use of the source reconstruction method to estimate incident field distributions in microwave imaging
Bibliographic record
Abstract
Microwave Imaging (MWI) is a modality that attempts to obtain the dielectric profile of an object of interest (OI) by exposing it to successive interrogation from a number of co-resident antennas. MWI is advantageous because it is noninvasive and non-ionizing, and consequently it is being used in areas such as biomedical imaging and industrial non-destructive testing. The performance of MWI is dependent, in part, on accurate knowledge of the incident field used to interrogate the OI. The antennas used in MWI systems are usually approximated by simple models, such as point sources, in order to reduce the cost of the numerical model (M. Ostadrahimi et. al., IEEE Antennas Wireless Propag. Lett., 10, 900–903, 2011). This results in the incident field being approximated, and thus, calibration techniques are necessary to compensate for the modelling error. This can lead to degraded reconstructed image quality or additional time consuming measurements needed for calibration.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".