Sonographic Examination of the Carotid Arteries
Bibliographic record
Abstract
Ultrasonography (US) of the carotid arteries is a common imaging study performed for diagnosis of carotid artery disease. In the United States, carotid US may be the only diagnostic imaging modality performed before carotid endarterectomy. Therefore, the information obtained with carotid US must be reliable and reproducible. Technical parameters that can affect the accuracy of carotid US results include the Doppler angle, sample volume box, color Doppler sampling window, color velocity scale, and color gain. Important factors in diagnosis of atherosclerotic disease of the extracranial carotid arteries are the intima-media thickness, plaque morphology, criteria for grading stenosis, limiting factors such as the presence of dissection or cardiac abnormalities, distinction between near occlusion and total occlusion, and the presence of a subclavian steal. Challenges to the consistency of carotid US results may include lack of a standard protocol, poor Doppler technique, inexperience in interpretation of hemodynamic changes reflected in the Doppler waveform, artifacts, and physical challenges. Hindrances in the classification of problematic carotid artery stenoses may be overcome by following a standard protocol and optimizing scanning techniques and Doppler settings.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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".