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Record W1561183469 · doi:10.3390/su7089787

The Toledo Drinking Water Advisory: Suggested Application of the Water Safety Planning Approach

2015· article· en· W1561183469 on OpenAlex

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueSustainability · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicWater Quality and Pollution Assessment
Canadian institutionsMcMaster University
FundersNatural Sciences and Engineering Research Council of CanadaHealth Canada
KeywordsContext (archaeology)EutrophicationEnvironmental planningCorporate governanceBusinessWater safetyWater treatmentWater resource managementEnvironmental protectionEnvironmental scienceEnvironmental engineeringWater qualityGeographyFinanceEcologyBiology

Abstract

fetched live from OpenAlex

On 2 August 2014 the city of Toledo, in Ohio USA issued a “do not drink” water advisory and declared a state of emergency. This was as a result of elevated levels of the toxin microcystin in the final treated water, a dangerous toxin produced by the algae cyanobacteria. The Toledo water crisis is a key focusing event that can advance dialogue on eutrophication governance in the context of public health. This paper examines the Toledo water ban with the aim of determining whether this crisis could have been averted. Further, we explore how this event can be used to stimulate action on eutrophication governance, to motivate action to protect water at its source. We use the World Health Organization’s Water Safety Planning Methodology to show that the crisis could have been averted with some simple risk management actions. We also show that a water safety planning approach could lead to well developed operational and maintenance planning resulting in a higher probability of safe drinking water.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.348
Threshold uncertainty score0.300

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.018
GPT teacher head0.270
Teacher spread0.252 · 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