Water-in-water droplet microfluidics: A design manual
Bibliographic record
Abstract
Droplet microfluidics is utilized in a wide range of applications in biomedicine and biology. Applications include rapid biochemical analysis, materials generation, biochemical assays, and point-of-care medicine. The integration of aqueous two-phase systems (ATPSs) into droplet microfluidic platforms has potential utility in oil-free biological and biomedical applications, namely, reducing cytotoxicity and preserving the native form and function of costly biomolecular reagents. In this review, we present a design manual for the chemist, biologist, and engineer to design experiments in the context of their biological applications using all-in-water droplet microfluidic systems. We describe the studies achievable using these systems and the corresponding fabrication and stabilization methods. With this information, readers may apply the fundamental principles and recent advancements in ATPS droplet microfluidics to their research. Finally, we propose a development roadmap of opportunities to utilize ATPS droplet microfluidics in applications that remain underexplored.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 0.019 |
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".