Non-Gaussian statistics and temporal variations of the ultrasound signal backscattered by blood at frequencies between 10 and 58 MHz
Bibliographic record
Abstract
Very little is known about the blood backscattering behavior and signal statistics following flow stoppage at frequencies higher than 10 MHz. Measurements of the radio frequency (rf) signals backscattered by normal human blood (hematocrit = 40%, temperature = 37 degrees C) were performed in a tube flow model at mean frequencies varying between 10 and 58 MHz. The range of increase of the backscattered power during red blood cell (RBC) rouleau formation was close to 15 dB at 10 and 36 MHz, and dropped, for the same blood samples, below 8 dB at 58 MHz. Increasing the frequency from 10 to 58 MHz raised the slope of the power changes at the beginning of the kinetics of aggregation, and could emphasize the non-Gaussian behavior of the rf signals interpreted in terms of the K and Nakagami statistical models. At 36 and 58 MHz, significant increases of the kurtosis coefficient, and significant reductions of the Nakagami parameter were noted during the first 30 s of flow stoppage. In conclusion, increasing the transducer frequency reduced the magnitude of the backscattered power changes attributed to the phenomenon of RBC aggregation, but improved the detection of rapid growth in aggregate sizes and non-Gaussian statistical behavior.
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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 | 0.003 |
| 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) | 0.000 | 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 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".