Effect of Cell Size for In-Flow Dielectrophoresis Cytometry-Based Dielectric Characterization
Bibliographic record
Abstract
In this work, we use a microfluidic flow cytometer for the simultaneous imaging and dielectric characterization of individual biological cells within a flow. Knowledge of cell size in conjunction with dielectric properties enhance the ability to characterize individual cells. A high-speed camera is used to capture and track multiple cells in real-time as they traverse a microfluidic channel. This channel incorporates a coplanar electrode array, which produces a non-uniform electric field, thereby introducing dielectrophoretic forces, and translating to higher or lower velocity. Multiphysics electrostatic-fluid dynamics simulation is employed to establish the relationship between cell velocity, differential velocity and size and the Clausius-Mossotti factor (CMF), which is a function of the cell's dielectric properties. The system is evaluated using polystyrene microspheres (PSS) and demonstrated using Chinese hamster ovary (CHO) cells.
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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 | 0.001 |
| 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) | 0.001 | 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".