MétaCan
Menu
Back to cohort
Record W2156824969 · doi:10.2471/blt.09.072512

Engaging with the water sector for public health benefits: waterborne pathogens and diseases in developed countries

2010· article· en· W2156824969 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.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueBulletin of the World Health Organization · 2010
Typearticle
Languageen
FieldNursing
TopicChild Nutrition and Water Access
Canadian institutionsnot available
FundersMedical Research CouncilNatural Environment Research CouncilCanadian Water NetworkSight Research UK
KeywordsWaterborne diseasesPublic healthEnvironmental healthDeveloping countryPublic sectorWater supplyMedicineBusinessEnvironmental protectionGeographyBiologyVirologyEnvironmental sciencePolitical scienceOutbreakEcologyEnvironmental engineeringNursing

Abstract

fetched live from OpenAlex

An editorial published in the Bulletin of the World Health Organization in 2008 argued for stronger engagement between the health and water sectors, commenting “a public health perspective in water management provides opportunities to both improve population health and reduce costs.” When viewed from a public health perspective, water is typically considered in terms of drinking, bathing and waste disposal but other activities, particularly food production, inshore fisheries and recreation, form important points of human contact. The water sector is diverse, comprising environmental sciences, engineering, the water supply industry, regulatory authorities and government policy-makers. A new level of engagement to involve the water sector in public health objectives is therefore dependent upon establishing a basis for dialogue and collaboration between these stakeholders, who bring widely differing conceptual approaches and practical concerns. In support of this aim, we present here a perspective on waterborne pathogens and diseases from a multidisciplinary expert group from the environmental science, microbiology, water industry, regulatory and health protection communities in the United Kingdom of Great Britain and Northern Ireland.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.540
Threshold uncertainty score0.509

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.016
GPT teacher head0.245
Teacher spread0.229 · 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