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Record W1992952231 · doi:10.1016/j.proenv.2010.10.142

Phytoremediation in Engineered Wetlands: Mechanisms and Applications

2010· article· en· W1992952231 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueProcedia Environmental Sciences · 2010
Typearticle
Languageen
FieldEnvironmental Science
TopicConstructed Wetlands for Wastewater Treatment
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsWetlandPhytoremediationEnvironmental scienceLeachateEnvironmental engineeringHeavy metalsWaste managementEngineeringEcologyEnvironmental chemistry

Abstract

fetched live from OpenAlex

Engineered wetland phytoremediation is an aesthetically pleasing, solar-driven, passive technique useful for cleaning up wastes including metals, pesticides, crude oil, polyaromatic hydrocarbons, and landfill leachates and has become an increasingly recognized pathway to advance the treatment capacity of wetland systems. This review addresses the mechanisms of phytoremediation in engineering wetland systems when reducing loads of various contaminants, as well as the application of phytoremediation as an environmentally sound technology in engineered wetland systems in both laboratory and field levels, followed by a case study of full scale application in Newfoundland, Canada. The review is expected to help add more capacity to understand phytoremediation in engineered wetland systems, and establish an effective framework for further applications.

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.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.203
Threshold uncertainty score0.721

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.004
GPT teacher head0.185
Teacher spread0.182 · 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