Turbulence intensity in a region of interest 2cm distal to the carotid bifurcation in a family of seven anthropomorphic flow phantoms
Bibliographic record
Abstract
An in vitro flow system has been used to assess the flow disturbances downstream of the stenosis in a family of seven carotid bifurcation phantoms modelling varying plaque build-up both axially symmetrically (concentrically) and asymmetrically (eccentrically). Radio frequency data were collected for 10 s at each of over 1000 sites within each model, and a sliding 1024-point FFT is applied to the data to extract the Doppler spectrum every 12 ms. From this, the ensemble average over 10 cardiac cycles of the spectral mean velocity, and the root mean square over these same 10 cardiac cycles - the turbulence intensity (TI), can be obtained as a function of an ensemble averaged cardiac cycle at each spatial point in all phantoms. TI was investigated by looking at the average over a 25 mm2 square region of interest in the ICA centered 2 cm distal to the apex of the bifurcation. TI in the region of interest increased with stenosis severity; at 23ms following peak systole, the time point when TI was maximal for the majority of models, this ranged from 2.4±0.1 cm/s in the non-diseased model to 6.6±0.3, 16.0±1.4 and 26.1±1.3 cm/s in the 30, 50 and 70% concentrically stenosed (by NASCET criteria) models, respectively. Similarly, TI was 8.3±0.7, 19.9±1.1, and 26.2±1.2 cm/s in the 30, 50 and 70% eccentrically stenosed models, respectively. Differences in TI between models, both in increasing stenosis severity and between eccentricities, were statistically different except between the 70% concentric and eccentric models.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".