Ultrasound characterization of coronary artery wall in vitro using temperature-dependent wave speed
Bibliographic record
Abstract
Temperature dependence of the speed of sound, partial partial differential c/partial partial differential T, is examined as a parameter to characterize tissue-equivalent phantoms and coronary artery tissue in vitro. The experimental system comprises an ultrasound biomicroscope, operating at center frequency of 50 MHz, and a temperature controlled micropositioning sample cell. Radio frequency (RF) backscattered signals were recorded, with a digital oscilloscope, from 64 independent positions and at 5 temperatures starting at 31 degrees C (phantom) and 36 degrees C (tissue) in steps of one degree. Time shift per degree Celsius (delta t/delta T) was obtained with a correlation technique applied between gated sections of two RF-signals collected with one degree temperature difference from the same location in the sample. The average (delta t/delta T), calculated for every position of the gated sections along the propagation axis of the ultrasound beam, has the slope proportional to the difference between the linear coefficient of thermal expansion and the thermal sensitivity of the speed of sound. Calibration measurements of partial partial differential c/partial partial differential T, made with single- and three-layer tissue equivalent phantoms, correlated well (r > or = 0.91) with those measured by the time-of-flight substitution method. The partial partial differential c/partial partial differential T was estimated for the three layers on the wall of eight samples of human coronary arteries, obtained at autopsy from four individuals. The partial partial differential c/partial partial differential T for the intima layers decreases as the disease progresses from mild intimal thickening to a more advanced atherosclerosis.
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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) | 0.000 | 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".