Digital microfluidic operations on micro-electrode dot array architecture
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
As digital microfluidics-based biochips find more applications, their complexity is expected to increase significantly owing to the trend of multiple and concurrent assays on the chip. There is a pressing need to deliver a top-down design methodology that the biochip designer can leverage the same level of computer-aided design support as the semi-conductor industry now does. Moreover, as microelectronics fabrication technology is scaling up and integrated device performance is improving, it is expected that these microfluidic biochips will be integrated with microelectronic components in next-generation system-on-chip designs. This study presents the analysis and experiments of digital microfluidic operations on a novel electrowetting-on-dielectric-based 'micro-electrode dot array architecture' that fosters a development path for hierarchical top-down design approach for digital microfluidics. The proposed architecture allows dynamic configurations and activations of identical basic microfluidic unit called 'micro-electrode cells' to design microfluidic components, layouts, routing, microfluidic operations and applications of the biochip hierarchically. Fundamental microfluidic operations have been successfully performed by the architecture. In addition, this novel architecture demonstrates a number of advantages and flexibilities over the conventional digital microfluidics in performing advanced microfluidic operations.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| 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) | 0.000 | 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 it