Fast Three‐dimensional Numerical Hemolysis Approximation
Bibliographic record
Abstract
The in vivo implantation of a mechanical device contributes to hemodynamic disturbances, which are responsible for damage to the membranes of red blood cells that in turn can lead to their rupture (hemolysis). It is important to ascertain at the design stage of such mechanical devices that they are innocuous to blood. Because there is no in vivo hemolysis index, we concentrated our efforts on the in vitro hemolysis index of the American Society for Testing and Material (ASTM) standard. We present in this work a framework for minimizing medical device-induced hemolysis by the development of a numerical method for predicting hemolysis similar to that used in in vitro experiments. The method is based on a novel interpretation of the Giersiepen-Wurzinger blood damage correlation that replaces the computation of blood damage along the streamline by a volume integration of a damage function over the computational domain. We assess the behavior and accuracy of this methodology with 3D examples.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".