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Record W2067077896 · doi:10.2166/wst.2015.102

Pathogen removal from domestic and swine wastewater by experimental constructed wetlands

2015· article· en· W2067077896 on OpenAlexaff
Germán Giácoman‐Vallejos, Carmen Ponce‐Caballero, Pascale Champagne

Bibliographic record

VenueWater Science & Technology · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicConstructed Wetlands for Wastewater Treatment
Canadian institutionsQueen's University
FundersConsejo Nacional de Ciencia y Tecnología
KeywordsTyphaFecal coliformWastewaterMacrophyteWetlandChemical oxygen demandEnvironmental scienceTotal suspended solidsEnvironmental engineeringSalmonellaVeterinary medicineBiologyWater qualityEcologyBacteriaMedicine

Abstract

fetched live from OpenAlex

This study examined the performance of subsurface flow horizontal wetlands in total coliforms, faecal coliforms, enterococci and Salmonella removal from swine and domestic wastewaters. The effects of organic loading rate, contact time (CT) and the presence of aquatic macrophytes, Typha dominguensis and Typha latifolia, on treatment performance were evaluated. In general, chemical oxygen demand (COD) and total suspended solids (TSS) were reduced by 66 and 72% after 24 h and 75 and 84% after 48 h in domestic wastewaters, and 73 and 71% after 24 h and 72 and 78% after 48 h in swine wastewater. Total coliform and faecal coliform reductions of 70-83% and 65-78% were observed in the vegetated systems after 24 h of CT, while after 48 h, total coliform and faecal coliform reductions of 80-82% and 86-91% were noted.

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 score0.003
Threshold uncertainty score0.006

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)0.0000.000

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 head0.007
GPT teacher head0.218
Teacher spread0.210 · 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

Citations20
Published2015
Admission routes1
Has abstractyes

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