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Record W2040673012 · doi:10.2166/wqrjc.2013.132

Occurrence and predictive correlations of Escherichia coli and Enterococci at Sandpoint beach (Lake St Clair), Windsor, Ontario and Holiday beach (Lake Erie), Amherstburg, Ontario

2013· article· en· W2040673012 on OpenAlexaffabout
Kerry N. McPhedran, Rajesh Seth, Rajesh S Bejankiwar

Bibliographic record

VenueWater Quality Research Journal · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicFecal contamination and water quality
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsIndicator bacteriaEnvironmental scienceTurbidityWindsorFecal coliformContaminationPollutionNonpoint source pollutionHydrology (agriculture)EcologyWater qualityBiology

Abstract

fetched live from OpenAlex

Point and nonpoint sources contribute to fecal contamination of surface waters by human pathogens that exist at low concentrations and are difficult, expensive, and/or impossible to easily detect. Therefore, fecal indicator bacteria (FIB) are used as surrogates in identification of fecal contamination, including Escherichia coli (EC) and Enterococcus spp. (ENT), at recreational beaches to protect from adverse health effects from exposure to water-borne pathogens. The objective of the current study was to conduct a preliminary investigation of the environmental processes contributing to the nature and significance of FIB (EC and ENT) over 30 d at Sandpoint beach (Windsor, Ontario) and Holiday beach (Amherstburg, Ontario). Daily, three 100 mL samples were collected for EC and ENT for analysis by Colilert® and Entrolert®, respectively. Additionally, physicochemical and hydrometerological data were measured or taken from data archives. Both EC and ENT populations were dynamic and well correlated to each other (p < 0.05; analysis of variance (ANOVA)) and both FIB correlated with turbidity and wave height (p < 0.10; ANOVA). Despite being geographically close and therefore having similar meteorological data, both beaches exhibited markedly different FIB, turbidity and wave height data, suggesting that beach-specific data should be considered for any future predictive applications.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.683
Threshold uncertainty score0.988

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0130.000

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.

Opus teacher head0.059
GPT teacher head0.312
Teacher spread0.254 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations7
Published2013
Admission routes2
Has abstractyes

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