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Record W1967456342 · doi:10.1890/070110

Constructed wetlands in China: recent developments and future challenges

2008· review· en· W1967456342 on OpenAlexafffund
Dong Liu, Ying Ge, Jie Chang, Changhui Peng, Binhe Gu, Yuk Sing Gilbert Chan, Xiaofu Wu

Bibliographic record

VenueFrontiers in Ecology and the Environment · 2008
Typereview
Languageen
FieldEnvironmental Science
TopicConstructed Wetlands for Wastewater Treatment
Canadian institutionsUniversité du Québec à Montréal
FundersNational Natural Science Foundation of ChinaCanada Research Chairs
KeywordsWetlandChinaGovernment (linguistics)Ecological engineeringInvestment (military)Environmentally friendlyEnvironmental planningBusinessEmerging technologiesEnvironmental scienceSewage treatmentEnvironmental resource managementEnvironmental economicsRisk analysis (engineering)Computer scienceEnvironmental engineeringEcologyPolitical scienceEconomics

Abstract

fetched live from OpenAlex

Constructed wetlands (CWs) are an emerging, environmentally friendly engineering system employed in China. They require lower investment and operation costs while providing higher treatment efficiency and more ecosystem services than conventional wastewater treatment methods. Introduced to China in 1987, CW systems used for wastewater treatment have rapidly increased in number, particularly since the late 1990s. This review summarizes the state‐of‐the‐art application of CW systems for water pollution treatment by reviewing the basics of the technology and its historical development and performance efficiency. Current progress, limitations, future concerns, and the challenges of CW technologies are also discussed. Also highlighted is the need for sufficient and appropriate data to assist in the further development of CW systems and the implementation of integrated “bottom‐up” and “top‐down” approaches by both the public in general and government bodies in particular.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.012
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.004
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.008
GPT teacher head0.202
Teacher spread0.194 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations122
Published2008
Admission routes2
Has abstractyes

Explore more

Same venueFrontiers in Ecology and the EnvironmentSame topicConstructed Wetlands for Wastewater TreatmentFrench-language works237,207