An integrated microchip for dielectrophoresis based characterization and manipulation of cells
Bibliographic record
Abstract
In the past, a variety of complementary techniques such as dielectrophoretic levitation, electrorotation and travelling wave dielectrophoresis (TWD) have each been individually and effectively applied in demonstrating the promising applications of DEP in the life and biological science. In this regard, however, little effort has been devoted to the development of an integrated platform that enables simultaneous such manipulations and measurements on a single microfabricated chip. In this paper we discuss the design and implementation of a single microchip (3 mm/spl times/6 mm) onto which three types of microelectrodes of similar geometric layouts but various functions were integrated. Yeast and plant protoplasts known to have well-characterized dielectric properties as test particles were used to investigate the electrokinetic behaviors for these electrodes as a function of frequency and electrode excitation mode. Several characteristic cell electrokinetic behaviors were identified, including linear conveyance, electrorotation and levitation in different regions of the frequency spectrum. The experimental observations demonstrated the feasibility and adaptability of combining the three main electrokinetic effects of DEP as a system on a single microchip platform in a compact manner.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".