An Evaluation of Microbial Contamination in Ontario Beach Waters: qPCR Vercus Culture for Enterococcus
Bibliographic record
Abstract
Contamination in recreational beach water is currently assessed using culture-based measurements of fecal indicator bacteria, a process that requires eighteen to twenty-four hours, from the time of sample collection until results can be released (Converse 2012). Due to the fluctuating nature of microbial contamination, data obtained twenty-four hours later are barely pertinent, and decisions regarding beach closure must be made on outdated information. To avoid this lag, real time polymerase chain reaction (qPCR) has been suggested as an alternate testing method, since it directly measures the genetic material in a sample, and thus can reduce lag time to about three to four hours (Ferretti 2010). The major concern of using qPCR is that the value obtained is a measure of DNA in a sample, and, even though the value can be compared to the amount of DNA in one cell, there may be DNA in the sample that should not be counted towards the total, such as DNA from dead organisms (Haugland 2005). This paper focuses on samples collected during the summer of 2012 from Outlet Beach and Bath Filtration Plant in Kingston, Ontario. DNA was extracted from the samples and subjected to qPCR. The amount of DNA was then compared to a known amount of DNA in calibrator cells. This calculated calibrator cell equivalent value can then be compared to the colony forming unit value, as determined by membrane filtration. Through statistical analysis, a relationship can then be found between the two related values.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".