A hydrogel based rapid test method for detection of Escherichia coli (E. coli) in contaminated water samples
Bibliographic record
Abstract
We have formulated a new chemical composition for rapid detection of Escherichia coli (E. coli) with currently available enzymatic substrates. We have evaluated the performance of the new chemical composition with different kinds of bacteria, and metallic and ionic interferences and optimized the chemical composition for rapid and specific detection of E. coli. We used a novel hydrogel based porous matrix to encapsulate the optimized chemical compounds and incorporated it within a readily available plunger-tube assembly. This overall system allows efficient, field deployable, rapid testing of water samples by simultaneously pre-concentrating and detecting E. coli within one integrated unit. We were able to detect E. coli concentrations of 4 × 10(6) CFU mL(-1) to 4 × 10(5) CFU mL(-1) within 5 min and 4 × 10(4) CFU mL(-1) to 400 CFU mL(-1) within 60 min using the integrated plunger-tube assembly containing the hydrogel matrix.
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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".