A Two-Phase Core-Plasma Model for Microvascular Blood Flow: Comparative Analysis of Hemodynamic Models
Bibliographic record
Abstract
Abstract Microcirculatory blood flow exhibits complex non-Newtonian behavior, including shear-thinning properties and the formation of a cell-free layer (CFL)—a plasma-rich region near vessel walls. While traditional rheological models such as Newtonian, Power Law, and Carreau describe certain flow characteristics, and empirical models like the double-parameter power fit have been used to capture velocity profiles, these approaches fall short in fully characterizing the dynamic interplay between red blood cells (RBCs) and plasma. This study introduces the Core-Plasma Model, a two-phase framework that integrates Newtonian and non-Newtonian elements to represent the RBC-rich core and surrounding CFL. In vitro experiments in 25 µ m and 50 µ m round channels across varying flow rates, hematocrit levels (5–20%), and suspending media (PBS and native plasma) demonstrate the model’s superior ability to capture velocity and shear rate profiles. The Core-Plasma Model offers a robust platform for advancing microscale hemodynamic predictions and deepening the understanding of microvascular flow dynamics.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".