Optimization of Blood Microfluidic Co-Flow Devices for Dual Measurement
Bibliographic record
Abstract
Microfluidics is a prominent field used to analyze small amounts of biological fluids. Co-Flow microfluidic devices can be used to study red blood cell aggregation in blood samples under a controlled shear rate. The purpose of this paper is to optimize the parameters of a co-flow device in order to produce a linear velocity profile in blood samples which would provide a constant shear rate. This is desired as the eventual goal is to use an ultrasonic measurement sensor with the co-flow microfluidic device to analyze red blood cell aggregates. Computational fluid dynamic simulations were performed to model a microfluidic device. The simulation results were verified by μPIV of the experimental microfluidic device. Modifications were made to the geometry and flow rate ratio of the microfluidic device to produce a more linear velocity profile. By using a flow rate ratio of 50:1 of shearing fluid to sheared fluid, we were able to achieve a velocity profile in the blood layer that is approximately linear.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".