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Urban Runoff Quality Characterization and Load Estimation in Saskatoon, Canada

2006· article· en· W2161462647 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.

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

VenueJournal of Environmental Engineering · 2006
Typearticle
Languageen
FieldEnvironmental Science
TopicUrban Stormwater Management Solutions
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsSurface runoffEnvironmental scienceWater qualityUrban runoffTotal suspended solidsHydrology (agriculture)Nonpoint source pollutionPollutantSuspended solidsStormwaterBiochemical oxygen demandEnvironmental engineeringChemical oxygen demandEffluentRunoff curve numberCombined sewerSewage treatmentWastewaterEcologyEngineering

Abstract

fetched live from OpenAlex

The improvement in the effluent quality of the treated sanitary sewage entering the South Saskatchewan River at Saskatoon, Canada, and the impending change in provincial legislation governing urban runoff, provided the impetus for Saskatchewan Environment to initiate the stormwater runoff quality study reported in this paper. Among others, the study involved a field program for characterizing the urban runoff water quality from four catchments, each representing a different type of land use. Both a site mean concentration approach and a multiple variable regression analysis approach were used to quantify the pollutant load contained within the runoff. Thereafter, using the runoff water quality characterizations developed in the study, rainfall–runoff pollutant loads from the entire city were estimated and compared with two local point sources to the receiving stream. On the basis of this analysis, it was found that urban runoff contributes more total suspended solids and total Kjeldahl nitrogen load, similar chemical oxygen demand load, and slightly less total phosphorus load than the two local point sources.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.456
Threshold uncertainty score0.998

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 head0.003
GPT teacher head0.158
Teacher spread0.155 · 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