Fluorescent Carrier Ampholytes Assay for Portable, Label-Free Detection of Chemical Toxins in Tap Water
Bibliographic record
Abstract
We present a novel method for fluorescence-based indirect detection of analytes and demonstrate its use for label-free detection of chemical toxins in a hand-held device. We fluorescently label a mixture of low-concentration carrier ampholytes and introduce it into an isotachophoresis (ITP) separation. The carrier ampholytes provide a large number of fluorescent species with a wide range of closely spaced effective electrophoretic mobilities. Analytes focus under ITP and displace subsets of these carrier ampholytes. The analytes are detected indirectly and quantified by analyzing the gaps in the fluorescent ampholyte signal. The large number (on the order of 1000) of carrier ampholytes enables detection of a wide range of analytes, requiring little a priori knowledge of their electrophoretic properties. We discuss the principles of the technique and demonstrate its use in the detection of various analytes using a standard microscope system. We then present the integration of the technique into a self-contained hand-held device and demonstrate detection of chemical toxins (2-nitrophenol and 2,4,6-trichlorophenol) in tap water, with no sample preparation steps.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".