Optofluidic Detection of Aqueous Ammonia and Parasitic Cysts
Bibliographic record
Abstract
Water quality monitoring in Canada is essential to providing safe water to all. Indigenous and remote communities, many of which are under boiling drinking water advisories, lack availability and/or funding to water monitoring resources. A low-cost, point-of-care detection mechanism has been proposed for the detection of aqueous ammonia and protozoan parasites, which affect the safety of a source of water. An ammonia fluorescence responsive hydrogel, based on the fluorescence quenching of rare earth metal Europium (Eu3+) upon contact with aqueous ammonia, has been proposed to be incorporated into a microfluidic device, which utilizes shadow imaging and flow analysis to detect parasitic (oo)cysts of Cryptosporidium and Giardia, two of the most prevalent protozoan parasites which cause gastrointestinal illness around the world. Fabrication of the ammonia sensitive hydrogel was completed, and the essential components to the ammonia sensitivity were determined. Chemical analysis and solvent modifications found that Formamide is the essential solvent to maintain ammonia sensitivity. A literature review into the current detection mechanisms of Cryptosporidium and Giardia was completed to provide a reference and starting point for the development of the low-cost, point-of-care device proposed in this thesis. Baseline images of Cryptosporidium parvum and Giardia lamblia were captured to provide a reference for the development of a particle tracking algorithm to be used in the microfluidic device. The images captured highlight morphological features essential to developing a tracking mechanism based on the morphology of the (oo)cysts.
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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 | 0.000 |
| 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) | 0.001 | 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 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".