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Record W2310406202 · doi:10.14796/jwmm.c396

The Water Utility Risk Integration Matrix: Demonstrating Potential for an Integrated Approach to Municipal Water Management

2016· article· en· W2310406202 on OpenAlexaffvenueabout
M. de Lange, Richard Harvey, Yi Wang, Edward A. McBean

Bibliographic record

VenueJournal of Water Management Modeling · 2016
Typearticle
Languageen
FieldEngineering
TopicWater resources management and optimization
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsIsolation (microbiology)Risk analysis (engineering)BusinessRisk managementMatrix (chemical analysis)Environmental planningWater resource managementEnvironmental scienceEnvironmental resource managementFinanceChemistry

Abstract

fetched live from OpenAlex

Municipal water utilities traditionally have been managed in isolation with little consideration of common factors affecting risk. An integrated approach to municipal water management has great potential for increasing the resilience of these systems under future uncertainties. In a recent survey conducted by the University of Guelph, respondents from various Canadian municipalities identified aging infrastructure, climate change and urbanization as the top three drivers of risk to water infrastructure. To demonstrate the potential for an integrated approach to risk management of water infrastructure, the Water Utility Risk Integration Matrix document was developed. This interactive document emphasizes commonalities across municipal water sectors and allows users to quickly access relevant information on the previously identified drivers of risk. Each chapter provides an overview of the impact each driver has on water treatment and distribution, sewage conveyance and treatment, combined sewer systems, and stormwater conveyance.

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)0.002
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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.739
Threshold uncertainty score0.504

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 communication0.0000.001
Open science0.0010.000
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 head0.019
GPT teacher head0.224
Teacher spread0.206 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations3
Published2016
Admission routes3
Has abstractyes

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