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Record W2272293496

Groundwater Quality in Canada: A National Overview

2007· article· en· W2272293496 on OpenAlexaboutno aff
Suzanne Lesage

Bibliographic record

VenueTunnelling and Underground Space Technology · 2007
Typearticle
Languageen
FieldEnvironmental Science
TopicGroundwater flow and contamination studies
Canadian institutionsnot available
Fundersnot available
KeywordsWater qualityEnvironmental planningAquiferGroundwaterWater resourcesBusinessGovernment (linguistics)Geological surveyPopulationWater supplyNatural resourceWater resource managementEnvironmental resource managementEnvironmental scienceEngineeringEnvironmental healthEnvironmental engineeringPolitical scienceLaw
DOInot available

Abstract

fetched live from OpenAlex

In Canada, drinking water quality is largely under provincial jurisdiction, with the Federal Government being responsible for the First Nations and Inuit as well as trans-boundary issues. The Guidelines for Canadian Drinking Water Quality set out the basic parameters that every water system (public, semi-public and private) should strive to achieve in order to provide a clean, safe and reliable drinking water supply. Because of the vast surface water resources in the country, public perception is often biased into thinking that these are sufficient. However, more than 30% of the Canadian population uses groundwater as their drinking water source. Until the recent worldwide trend in drinking bottled water, there was little interest in assessing the overall extent and quality of this resource in Canada. The advent of large bottling operations, with the associated problems in aquifer capacity and boundary issues, has changed the situation. The mapping of aquifers has been undertaken by Natural Resources Canada, whereas groundwater quality is a shared responsibility between Environment and Health Canada. A national survey of Federal contaminated sites was completed and an action plan for remediation is in place. A survey was conducted to delineate the magnitude of the threats to groundwater resources and to use the information in integrated watershed management plans.

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)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.340
Threshold uncertainty score0.533

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 studies0.0000.000
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 head0.024
GPT teacher head0.261
Teacher spread0.237 · 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 designObservational
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
Published2007
Admission routes1
Has abstractyes

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