Development of a Fully Monolithic Microfluidic Device for Complete Blood Count
Bibliographic record
Abstract
This thesis describes a monolithic microfluidic device capable of complete blood constituent enumeration from whole blood. For the first time, on-chip sample processing (e.g. dilution, lysis, and filtration) and downstream single cell analysis were fully integrated on device to enable complete blood cell count. The microfluidic device consists of two parallel sub-systems that perform sample processing and electrical analysis for simultaneous measurement of red (RBC) and white blood cell (WBC) parameters. The system provides a modular and adaptable environment capable of handling solutions of various viscosities and mixing ratios and features a new `offset' filter configuration for increased experimental duration. RBC concentration, mean corpuscular volume (MCV), cell distribution width, WBC concentration and differential are determined by electrical impedance measurements. Experimental characterization results of 97,305 WBCs and 104,735 RBCs from 10 patient blood samples demonstrate that the system is capable of performing high volume enumeration and complete blood count with accuracy.
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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 | 0.001 | 0.000 |
| 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".