Flow patterns and preferred sites of atherosclerotic lesions in the human aorta – I. Aortic arch
Bibliographic record
Abstract
OBJECTIVES: To elucidate the role of fluid mechanical factors in the localized genesis and development of atherosclerotic lesions in man. METHODS: Flow patterns and preferred sites of atherosclerotic lesions in the human aortic arch were studied in detail using isolated transparent aortic trees prepared from humans postmortem and by means of flow visualization of tracer polystyrene microspheres, using cinemicrographic techniques. RESULTS: Under the condition of steady flow that simulated mid-systole, the flow in the aortic arch consisted of three major components; (i) a straight flow to the brachio-cephalic artery located close to the right dorsal wall of the ascending aorta; (ii) a quasi-parallel undisturbed flow located close to the common median plane of the aortic arch and its side branches, and (iii) a clockwise slow, spiral secondary flow located dominantly near the left ventral wall of the aortic arch. Thus, looking down the aorta from its origin, the flow in the aortic arch appeared as a single helical flow revolving in a clockwise direction. CONCLUSIONS: Atherosclerotic lesions were found mainly in regions of low wall shear stress such as the proximal lip of the orifice of each side branch where a slow recirculation flow formed, and the left ventral wall of the aortic arch where a slow spiral secondary flow formed.
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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 | 0.000 |
| 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".