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Record W2132152764 · doi:10.2166/wqrj.2003.021

Windsor Combined Sewer Overflow Treatability Study with Chemical Coagulation

2003· article· en· W2132152764 on OpenAlexafffundabout
Jianguo Li, Samir Dhanvantari, David Averill, Nihar Biswas

Bibliographic record

VenueWater Quality Research Journal · 2003
Typearticle
Languageen
FieldEnvironmental Science
TopicUrban Stormwater Management Solutions
Canadian institutionsQuest University CanadaUniversity of Windsor
FundersGovernment of Canada
KeywordsSettlingWindsorSewageEnvironmental scienceEnvironmental engineeringCoagulationSewage treatmentWater columnPulp and paper industryGeologySoil scienceOceanographyEngineering

Abstract

fetched live from OpenAlex

Abstract Long column settling and jar tests were undertaken as part of a treatability study of combined sewage at the Lou Romano Water Reclamation Plant (LRWRP) in Windsor, Ontario. Different types of cationic polymers were examined in jar tests, and the appropriate dosage and its relationship with the TSS removal were determined for the polymer coagulation process. Settling column tests were used to develop settling rate distribution curves under both chemically aided and unaided conditions, and to examine the performance of polymer coagulation in improving the settleability of wet-weather sewage during CSO events. The results of the long column settling tests for settling rate distributions show that the characteristics of the wet-weather sewage at the LRWRP during CSO events were similar to those of samples collected at actual overflow sites along the Windsor Riverfront. Settling rate distributions demonstrated that polymer addition to the wet-weather sewage significantly improved the settling characteristics.

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 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)0.009
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.028
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.100
GPT teacher head0.365
Teacher spread0.265 · 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 teacher head, not a consensus.

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 routes3
Has abstractyes

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