Monitoring electric field induced changes in biological tissues and phantoms using ultrasound
Bibliographic record
Abstract
An external electric field can induce mechanical changes depending on the amplitude, frequency and duration of the applied electric field. This study is focused on monitoring the electric/electro-kinetic effects of real biological tissues (in vitro) and gelatin phantoms with high spatial resolution. In this study, we investigated the mean of the signal spectrum at the modulation frequency, root-mean-square of the noise in the spectrum, and signal-to-noise ratio (SNR) during the application of low-frequency AC electric field in tissues and phantoms. Our results show that the EIMC SNR can indicate the existence of AC electric current in samples, rather than be directly related to the sample's electro-kinetic properties of the samples. We also found that the SNR varies spatially even for homogenous samples. These two features might hinder the development of the proposed method to be a viable clinical diagnostic technique.
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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 | 0.000 | 0.001 |
| 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".