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Record W4226154686 · doi:10.5864/d2022-003

Beach water monitoring practices and challenges in Ontario Public Health units

2022· article· en· W4226154686 on OpenAlex
Cole Heasley, Johanna Sanchez, Ian Young, Jordan Tustin

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
venuePublished in a venue whose home country is Canada.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueEnvironmental Health Review · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicFecal contamination and water quality
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsRecreationWater qualityPublic healthEnvironmental resource managementFlexibility (engineering)Environmental planningGeographySampling (signal processing)Environmental healthEnvironmental scienceMedicineEngineeringPolitical scienceEcologyNursing

Abstract

fetched live from OpenAlex

Public Health Units (PHUs) in Ontario regularly monitor public beaches for E. coli levels as an indicator of the risk of recreational water-induced illness. Provincial guidance for beach water monitoring allows local flexibility in the beach monitoring process. We conducted a survey of public health professionals responsible for beach water management in Ontario PHUs to determine how monitoring practices differ across jurisdictions. We obtained data from 22 of the 29 PHUs that conduct beach water monitoring. Six health units reported meeting guidelines (27%) and four reported meeting historical water quality (18%) were important factors in deciding sampling frequency. Major challenges and limitations in monitoring that arose from the lag time between sampling and obtaining results were reported by 12 (55%). Predictive modelling has been trialled eight times across the province with varied results. This study provides an overview on the current state and future avenues for beach water monitoring in Ontario.

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.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.699
Threshold uncertainty score0.998

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.349
GPT teacher head0.349
Teacher spread0.000 · 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