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Record W3033262215 · doi:10.1002/awwa.1519

Developing Quebec's Water Efficiency Strategy

2020· article· en· W3033262215 on OpenAlexaboutno aff
Yannis Kachani, Mathieu Laneuville, Will Jernigan

Bibliographic record

VenueAmerican Water Works Association · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Policy and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsGeneral partnershipWater efficiencySustainabilityBusinessWater resourcesGovernment (linguistics)Environmental economicsIndex (typography)Water industryKey (lock)Environmental scienceEnvironmental resource managementEnvironmental planningWater supplyEnvironmental engineeringFinanceEconomicsComputer science

Abstract

fetched live from OpenAlex

Key Takeaways Launched in 2011 by the Quebec provincial government in partnership with its municipalities, the Quebec Water Efficiency Strategy aims to improve water use efficiency. The Quebec government now uses the infrastructure leakage index, the ratio of current annual volume of real losses to unavoidable annual volume of real losses, as a key performance indicator. The Quebec Water Efficiency Strategy will help cities better understand their infrastructure assets to help ensure sustainability of water services in a time of increased pressure on water resources.

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)0.000
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.802
Threshold uncertainty score0.884

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.017
GPT teacher head0.269
Teacher spread0.251 · 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 designNot applicable
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

Citations0
Published2020
Admission routes1
Has abstractyes

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