Bibliographic record
Abstract
MEMS-based microneedles have the potential to revolutionize biomedical/biotechnology applications by providing precise transdermal drug delivery and localized blood sampling. In this paper, we propose a novel theory-based model that predicts drift velocity of blood-flow through the microchannels embedded in the microneedles. The profile of blood flow in the microneedles is determined by solving the conservation of momentum equation of the liquid phase, coupled with the force balance equations at the liquid-air interface. For the first time, this work enables accurate calculation/prediction of the velocity profile of the blood flow through a vertical in-plane microneedle, considering the effect of surface tension forces which are the most prominent forces. In order to withdraw blood samples from capillaries in the dermis layer, the length of our MEMS-based in-plane microneedle has been set at 600 μm with the micro-channel thickness chosen to be 35 μm, to avoid deformation of red blood cells. Blood flow through microneedles has been computed analytically using the proposed formulation. The results are then verified by a commercial finite element simulation tool "ANSYS".
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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 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".