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Record W2151177235 · doi:10.2166/wst.2003.0078

Waste stabilisation ponds in extreme continental climates: a comparison of design methods from the USA, Canada, northern Europe and the former Soviet Union

2003· article· en· W2151177235 on OpenAlexaboutno aff
S. Heaven, A.C. Lock, L.N. Pak, M.K. Rspaev

Bibliographic record

VenueWater Science & Technology · 2003
Typearticle
Languageen
FieldEnvironmental Science
TopicIntegrated Water Resources Management
Canadian institutionsnot available
FundersU.S. Environmental Protection Agency
KeywordsSoviet unionEuropean unionNormativeClimate changeEnvironmental scienceEnvironmental protectionOceanographyPolitical scienceGeologyBusinessInternational tradeLaw

Abstract

fetched live from OpenAlex

The paper presents a brief review of the application of WSPs in extreme climates where ice formation occurs during winter. Design standards and methods are compared and different systems are described. Design equations developed by the US EPA and normative standards from the former Soviet Union are compared in a simple example using typical wastewater and performance characteristics. The results are similar except at low temperatures, where the Soviet method can give pond depths outside the prescribed limits. The paper examines construction and operational aspects of extreme climate WSPs, comparing North American, Northern European and Russian standards. It considers why WSP systems have not been widely adopted in Russia and the NIS, and looks at the advantages these systems may have in countries in economic transition.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.892
Threshold uncertainty score0.215

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.033
GPT teacher head0.255
Teacher spread0.221 · 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 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

Citations23
Published2003
Admission routes1
Has abstractyes

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