MétaCan
Menu
Back to cohort
Record W2598405052 · doi:10.1139/er-2016-0038

Artificial floating islands for water quality improvement

2017· article· en· W2598405052 on OpenAlexvenueno aff
Yueya Chang, He Cui, Yan He

Bibliographic record

VenueEnvironmental Reviews · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicConstructed Wetlands for Wastewater Treatment
Canadian institutionsnot available
Fundersnot available
KeywordsWetlandWater qualityEnvironmental scienceAquatic ecosystemNutrientComputer scienceEcologyBiology

Abstract

fetched live from OpenAlex

Artificial floating islands (AFIs) are a variation of wetland treatment systems for water quality improvement. This paper provides a review concerning AFIs in terms of their development, classification, and applications in the removal of nutrients, heavy metals, and chemical oxygen demand on waterways. The role of microorganisms, aquatic plants, and aquatic animals in AFIs for water decontamination and purification was also discussed. Additionally, some key factors influencing the AFIs’ performances were discussed and comparisons between AFIs and constructed wetlands were reviewed. Finally, further perspectives of artificial floating islands were identified to possibly improve their performances. The understanding of the mechanisms in AFIs that drive removal of various contaminants to improve water quality is crucial, and is also highlighted in this paper.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.561
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.002

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 head0.035
GPT teacher head0.293
Teacher spread0.258 · 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; both teacher heads agree on what is shown here.

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

Citations56
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueEnvironmental ReviewsSame topicConstructed Wetlands for Wastewater TreatmentFrench-language works237,207