Digital Microfluidic Method for Protein Extraction by Precipitation
Why this work is in the frame
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Bibliographic record
Abstract
We present the first microfluidic method for extracting proteins from heterogeneous fluids by precipitation. The new method comprises an automated protocol for precipitation of proteins onto surfaces, rinsing the precipitates to remove impurities, and resolubilization in buffer for further analysis. The method is compatible with proteins representing a range of different physicochemical properties, as well as with complex mixtures such as fetal bovine serum and cell lysate. In all cases, the quantitative performance (measured using a fluorescent assay for % recovery) was comparable to that of conventional techniques, which are manual and require more time. Thus, this work represents an important first step in efforts to develop fully automated microfluidic methods for proteomic analyses.
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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 | 0.000 |
| 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