Microfluidics for Processing Surfaces and Miniaturizing Biological Assays
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
Abstract This review is an account of our efforts to develop a versatile and flexible microfluidic technology for surface‐processing applications and miniaturizing biological assays. The review is presented in the context of current trends in microfluidic technology and addresses some of the major challenges for confining chemical and biochemical processes on surfaces: the sealing of a microchannel with a surface, the world‐to‐chip interface, the displacement of liquids in small conduits, the sequential delivery of multiple solutions, the accurate patterning of surfaces, the coincident detection of various analytes, and the detection of analytes in a small and dilute sample. Our solutions to these problems include the use of reversible sealing, capillary phenomena for powering and controlling liquid transport, and non‐contact microfluidics for spotting and drawing (on surfaces) with flow conditions. These solutions offer many advantages over conventional techniques for handling minute amounts of liquids and may find applications in lithography, biopatterning (e.g., the patterning of biomolecules), diagnostics, drug discovery, and also cellular assays.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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) | 0.000 | 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