Attractive Design: An Elution Solvent Optimization Platform for Magnetic-Bead-based Fractionation Using Digital Microfluidics and Design of Experiments
Bibliographic record
Abstract
There is great interest in the development of integrated tools allowing for miniaturized sample processing, including solid phase extraction (SPE). We introduce a new format for microfluidic SPE relying on C18-functionalized magnetic beads that can be manipulated in droplets in a digital microfluidic platform. This format provides the opportunity to tune the amount (and potentially the type) of stationary phase on-the-fly, and allows the removal of beads after the extraction (to enable other operations in same device-space), maintaining device reconfigurability. Using the new method, we employed a design of experiments (DOE) operation to enable automated on-chip optimization of elution solvent composition for reversed phase SPE of a model system. Further, conditions were selected to enable on-chip fractionation of multiple analytes. Finally, the method was demonstrated to be useful for online cleanup of extracts from dried blood spot (DBS) samples. We anticipate this combination of features will prove useful for separating a wide range of analytes, from small molecules to peptides, from complex matrices.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".