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Record W2076108088 · doi:10.1504/ijw.2007.015215

Controlling urban stormwater pollution by constructed wetlands: a Canadian perspective

2007· article· en· W2076108088 on OpenAlex
Allan S. Crowe, Quintin Rochfort, Kirsten Exall, J. Maršálek

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

VenueInternational Journal of Water · 2007
Typearticle
Languageen
FieldEnvironmental Science
TopicConstructed Wetlands for Wastewater Treatment
Canadian institutionsEnvironment and Climate Change Canada
Fundersnot available
KeywordsStormwaterWildlifeEnvironmental scienceWetlandHabitatWater qualityStormwater managementEnvironmental planningWater resource managementPollutionLand useEnvironmental resource managementEnvironmental engineeringSurface runoffEcologyCivil engineeringEngineering

Abstract

fetched live from OpenAlex

During the past 20 years, Constructed Stormwater Wetlands (CSWWs) have attained broad acceptance in Canada as effective measures for stormwater management. CSWWs are used mainly for improving stormwater quality by providing sufficient treatment volumes in shallow permanent pools. This leads to high requirements for land, which is one of the constraints on CSWWs use. Even though CSWWs perform less effectively in cold weather, through proper design they can be kept operational through the winter months. CSWWs attract wildlife, but do not provide high quality habitat. Consequently, CSWWs and their effects on wildlife need to be monitored and ecotoxicological risks controlled.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.541
Threshold uncertainty score0.999

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)0.0020.000

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 head0.004
GPT teacher head0.212
Teacher spread0.209 · 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