MétaCan
Menu
Back to cohort
Record W2018562391 · doi:10.1515/reveh.2008.23.2.119

Dealing with Waterborne Disease in Canada: Challenges in the Delivery of Safe Drinking Water

2008· review· en· W2018562391 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueReviews on Environmental Health · 2008
Typereview
Languageen
FieldEnvironmental Science
TopicFecal contamination and water quality
Canadian institutionsUniversity of British Columbia
FundersInstitute of Population and Public HealthInstitute of Circulatory and Respiratory HealthCancer Research Institute
KeywordsWaterborne diseasesScrutinyEnvironmental planningBusinessGovernment (linguistics)Environmental healthPublic healthOutbreakEnvironmental resource managementEnvironmental protectionMedicineEnvironmental sciencePolitical scienceNursing

Abstract

fetched live from OpenAlex

Protecting the public from waterborne diseases is an environmental health responsibility that every government worldwide must deal with. Canada's recent experience with waterborne outbreaks has brought the effectiveness of its water-monitoring and treatment systems under scrutiny. This paper focuses on microbial waterborne diseases and the shortcomings of drinking-water systems, dividing them into source control, monitoring, treatment, and operation, epidemiologic, and risk communication issues. Whereas some of these issues are often addressed, others, such as risk communication issues, are less frequently included in drinking water-management plans. Lessons can be learned from the Canadian experience, as these issues are applicable worldwide and especially in the developed world.

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)0.001
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: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.994
Threshold uncertainty score0.890

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.092
GPT teacher head0.292
Teacher spread0.200 · 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