Acoustic Characterization of Shell and Size Engineered Microbubbles
Bibliographic record
Abstract
Acoustically activated microbubbles are being used for molecular imaging, targeted drug delivery, and opening the impermeable blood-brain-barrier. However, our limited understanding of microbubble oscillation dynamics can hinder the ability to leverage their full potential in ultrasound applications. In the response to ultrasound, microbubble oscillations can be highly nonlinear, and the presence of a shell adds to the complexity of their oscillatory behavior, but previous models predicting microbubble behavior were based on linear assumptions. The focus of this project is to characterize the physical shell properties of microbubbles using attenuation measurements. The behavior of these microbubbles was observed to be linear at pressures between 4.6-10 kPa and they started to oscillate non-linearly at higher pressures. The estimated shell parameters suggest a higher shell elasticity at lower pressures and higher shell viscosity at higher pressure. Understanding microbubble behavior would help researchers to optimize the use of microbubbles and increase their therapeutic potential.
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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 | 0.000 | 0.001 |
| 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) | 0.001 | 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".