What do you mean by aortic valve area: geometric orifice area, effective orifice area, or gorlin area?
Bibliographic record
Abstract
Aortic valve area can be measured by cardiac catheterization, Doppler echocardiography, or imaging planimetry to assess aortic stenosis severity. These diagnostic techniques provide the Gorlin area, the effective orifice area (EOA) and the geometric orifice area (GOA), respectively. The differences between these three parameters depend mainly on the valve inflow shape and cross-sectional area of the ascending aorta. Because the values obtained may differ noticeably in the same patient, they may lead to different estimations of stenosis severity depending on the measurement method used. It is therefore essential to be aware of the underlying fundamentals on which these parameters are based. The aim of this state-of-the-art report was to clarify these hemodynamic concepts and to underline their clinical implications. Because planimetry only provides GOA and does not characterize the flow property, this method should preferably not be used to assess stenosis severity. The most appropriate parameters for this purpose are the Gorlin area and the energy loss coefficient (E(L)Co), which corresponds to the EOA adjusted for aortic cross-sectional area. From a hemodynamic viewpoint, Doppler E(L)Co and Gorlin area both reflect the fluid energy loss induced by aortic stenosis, and describe better the increased overload imposed on the left ventricle. Although the Gorlin area and Doppler E(L)Co are equivalent, the latter parameter has the advantage of being measurable non-invasively using Doppler echocardiography.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 teacher head, 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".