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Record W2921949595 · doi:10.5539/jas.v11n4p1

Restoration of On-farm Constructed Wetland Systems Used to Treat Agricultural Wastewater

2019· article· en· W2921949595 on OpenAlexafffundvenueabout
E. Smith, Lisa Kellman, Paul Brenton

Bibliographic record

VenueJournal of Agricultural Science · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicConstructed Wetlands for Wastewater Treatment
Canadian institutionsNova Scotia Department of AgricultureSt. Francis Xavier UniversityAgriculture and Agri-Food Canada
FundersAgriculture and Agri-Food CanadaDalhousie University
KeywordsWetlandAgricultureEnvironmental scienceWastewaterSewage treatmentConstructed wetlandEnvironmental engineeringWater resource managementEnvironmental planningEnvironmental resource managementGeographyEcology

Abstract

fetched live from OpenAlex

Two surface flow constructed wetland systems used to treat agricultural wastewater for over a decade were evaluated for their overall on-going treatment performance and future restoration need. Many on-farm constructed wetlands used for wastewater treatment in Atlantic Canada are now beginning to reach their saturation point and are no longer performing to their full operational potential. This study is an example of the process of evaluating when these systems are no longer viable; or are no longer functioning properly for wastewater treatment and outlines the steps necessary to restore their overall treatment capacities. On-farm constructed wetland restoration has been identified as a best management practice and can be accomplished successfully when important factors such as; landscape, hydrology, function, and the long-term farming goals are considered.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.709
Threshold uncertainty score0.438

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.009
GPT teacher head0.209
Teacher spread0.201 · 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.

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

Citations6
Published2019
Admission routes4
Has abstractyes

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