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Fast Three‐dimensional Numerical Hemolysis Approximation

2004· article· en· W2127354627 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueArtificial Organs · 2004
Typearticle
Languageen
FieldMedicine
TopicBlood transfusion and management
Canadian institutionsPolytechnique Montréal
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsHemolysisIn vivoComputationBiomedical engineeringMaterials scienceComputer scienceChemistryMedicineInternal medicineBiologyAlgorithm

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.296
Threshold uncertainty score0.957

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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.

Opus teacher head0.016
GPT teacher head0.243
Teacher spread0.226 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it