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Record W2039239174 · doi:10.2166/wst.2006.308

Water quality monitoring: the basis for watershed management in the Oldman River Basin, Canada

2006· article· en· W2039239174 on OpenAlex
C. Wendell Koning, Karen Anita Saffran, Joanne L. Little, Livio Fent

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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueWater Science & Technology · 2006
Typearticle
Languageen
FieldEnvironmental Science
TopicSoil and Water Nutrient Dynamics
Canadian institutionsAgriculture Food and Rural DevelopmentAlberta Environment and Protected Areas
Fundersnot available
KeywordsTributaryWater qualityWatershedHydrology (agriculture)RecreationSurface runoffWater resource managementStructural basinDrainage basinEnvironmental scienceWater resourcesAgricultureGeographyWatershed managementWater supplyIrrigationCryptosporidiumEcologyEnvironmental engineeringCartographyEngineeringGeology

Abstract

fetched live from OpenAlex

The Oldman River flows 440 km from its headwaters in south-western Alberta, through mountains, foothills and plains into the South Saskatchewan River. Peak flows occur in May and June. Three major reservoirs, together with more than a dozen other structures, supply water to nine irrigation districts and other water users in the Oldman basin. Human activity in the basin includes forestry, recreation, oil and gas development, and agriculture, including a large number of confined livestock feeding operations. Based on the perception of basin residents that water quality was declining and of human health concern, the Oldman River Basin Water Quality Initiative was formed in 1997 to address the concerns. There was limited factual information, and at the time there was a desire for finger pointing. Results (1998-2002) show that mainstem water quality remains good whereas tributary water quality is more of a challenge. Key variables of concern are nutrients, bacteria and pesticides. Point source discharges are better understood and better regulated, whereas non-point source runoff requires more attention. Recent data on Cryptosporidium and Giardia species are providing benefit for focusing watershed management activities. The water quality data collected is providing a foundation to implement community-supported urban and rural better management practices to improve water quality.

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: Empirical
Teacher disagreement score0.668
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0020.001
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 head0.010
GPT teacher head0.224
Teacher spread0.214 · 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