Validation of a novel vector method for blood peak velocity detection in an anthropomorphic phantom
Bibliographic record
Abstract
The peak blood velocity is a parameter of high medical interest, which is used, for example, in the determination of carotid stenosis grade. The standard approach, which typically exploits the maximum frequency detectable in the Doppler spectrum, is prone to two main sources of errors: the ambiguity of the Doppler angle and the spectral broadening. A novel method, based on a mathematical model, was recently introduced and shown to be unaffected by the spectral broadening. The method directly measures the maximum velocity component in a large sample volume that includes all the vessel section. Furthermore, its combination with a vector Doppler approach allows automatically correcting for the angle. This technique produced good results when verified in straight tubes, but tests in a more realistic configuration are necessary for an accurate validation. In this work, the proposed technique is compared against 2 already validated methods by investigating the common and internal branches of an anthropomorphic phantom, which mimics a carotid bifurcation with a 50% stenosis on the internal artery.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".