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Record W2099245119 · doi:10.1061/40792(173)164

Canada's CSO Technologies Manual — A Comprehensive Design and Resource Manual

2005· article· en· W2099245119 on OpenAlexfundaboutno aff
George Zukovs, Jiří Maršálek

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEnvironmental Science
TopicUrban Stormwater Management Solutions
Canadian institutionsnot available
FundersGovernment of Canada
KeywordsSustainabilityEmerging technologiesResource (disambiguation)Government (linguistics)Computer scienceEngineering managementRisk analysis (engineering)Environmental planningEngineeringBusinessEnvironmental science

Abstract

fetched live from OpenAlex

Municipal wastewater authorities are increasingly exploring new and innovative treatment technologies, which are specifically designed for combined sewer overflows (CSOs). When applied as part of an overall wastewater management strategy, these technologies can produce efficient and cost-effective solutions for CSOs. However, like all technologies they require systematic design and proper operation. In many cases, the basic information needed by municipal decision makers and their engineers to evaluate, select and design CSO treatment technologies has been difficult to assemble. In recognition of this need, the Government of Canada through the Great Lakes Sustainability Fund has recently developed a CSO Treatment Technologies Manual, which should serve to provide advice and guidance on the application of physical and physical-chemical technologies for the treatment of CSOs.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.521
Threshold uncertainty score0.965

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0060.006
Science and technology studies0.0030.001
Scholarly communication0.0030.002
Open science0.0030.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.1140.080

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 head0.013
GPT teacher head0.210
Teacher spread0.196 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreMethods

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
Published2005
Admission routes2
Has abstractyes

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