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Record W2479259281

Physicochemical Treatment of Combined Sewer Oveflow using Natural Polymers

2016· article· en· W2479259281 on OpenAlexaboutno aff
Omotola Hadizat Ajao

Bibliographic record

VenueScholarship at UWindsor (University of Windsor) · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicUrban Stormwater Management Solutions
Canadian institutionsnot available
Fundersnot available
KeywordsNatural (archaeology)Environmental scienceGeographyArchaeology
DOInot available

Abstract

fetched live from OpenAlex

The hazard posed by combined sewer overflow (CSO) to receiving water cannot be overemphasized due to its significant contribution of pollutants. Ontario’s Procedure F-5- 5 stipulates a minimum treatment limit of 50% reduction in suspended solids (SS) and 30% reduction in the 5-day biochemical oxygen demand (BOD5) for CSOs discharged in Ontario. The City of Windsor, Ontario, currently uses a synthetic polymer (Zetag 7873) for CSO treatment at its retention treatment basin (RTB) utilizing a physicochemical treatment method. Environmental persistence and potential toxicity are common concerns associated with synthetic polymers. These concerns may be limited when plant or animal based natural polymers are utilized. The effectiveness of commercially available natural polymers were evaluated for Windsor CSO treatment. The results show that Tanfloc SG was able to surpass the target of Procedure F-5-5 up to removal efficiencies of 91% and 56% for SS and BOD5 respectively for polymer dosages ranging between 5 mg/L – 30 mg/L.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.018
GPT teacher head0.210
Teacher spread0.191 · 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 designBench or experimental
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

Citations0
Published2016
Admission routes1
Has abstractyes

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