Investigation of cross talk in Kerfless annular arrays for high-frequency imaging
Bibliographic record
Abstract
The effect of electromechanical cross talk in high-frequency (> 30 MHz) kerfless annular arrays is investigated. Finite-element model predictions of the radiation patterns from arrays are compared to predictions from an ideal model without cross talk and with experimental measurements. High cross talk in the array causes element broadening and an increase in the amplitude of secondary lobes in the radiation pattern. However, an increase in the pulse ring-down time was not found. This can be attributed to the absence of lateral modes in the kerfless substrate. The level of the pedestal secondary lobes in the two-way radiation pattern increases linearly with the element path difference. The element broadening increases the effective element path difference, which increases the pedestal level for a kerfless annular array above the level for an ideal array. The broadening limits how close to an array one can image compared to the ideal case by reducing the contrast available in the image at small f-numbers. When the element broadening is taken into account by widening the electrode dimensions, the ideal radiation pattern agrees well with the finite-element model and experimental radiation patterns.
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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 | 0.001 | 0.002 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".