Counting-based microfluidic paper-based devices capable of analyzing submicroliter sample volumes
Why this work is in the frame
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Bibliographic record
Abstract
In this paper, we report the development of semiquantitative counting-based lateral flow assay (LFA)-type microfluidic paper-based analytical devices (μPADs) to analyze samples at submicroliter volumes. The ability to use submicroliter sample volumes is a significant advantage for μPADs since it enables enhanced multiplexing, reduces cost, and increases user-friendliness since small sample volumes can be collected using methods that do not require trained personnel, such as finger pricking and microneedles. The challenge of accomplishing a semiquantitative test readout using submicroliter sample volumes was overcome with a counting-based approach. In order to use submicroliter sample volumes, we developed a flow strategy with a running liquid to facilitate flow through the assay. The efficacy of the devices was confirmed with glucose and total human immunoglobulin E (IgE) tests using 0.5 μl and 1 μl of sample solutions, respectively. Semiquantitative results were generated to predict glucose concentrations in the range of 0–12 mmol/l and IgE concentrations in the range of 0–400 ng/ml. The counting-based approach correlates the number of dots that exhibited a color change to the concentration of the analyte, which provides a more user-friendly method as compared with interpreting the intensity of a color change. The devices reported herein are the first counting-based LFA-type μPADs capable of semiquantitative testing using submicroliter sample volumes.
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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 | 0.000 | 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