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Record W4239731806 · doi:10.1139/l00-091

Advanced technologies in water and wastewater treatment

2001· article· en· W4239731806 on OpenAlexvenueno aff
Haibo Zhou, Daniel W. Smith

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2001
Typearticle
Languageen
FieldEnvironmental Science
TopicMembrane Separation Technologies
Canadian institutionsnot available
Fundersnot available
KeywordsWastewaterFiltration (mathematics)Sewage treatmentWater treatmentEnvironmental scienceWaste managementEmerging technologiesIndustrial wastewater treatmentProcess engineeringEnvironmental engineeringEngineeringBiochemical engineeringNanotechnologyMaterials science

Abstract

fetched live from OpenAlex

The use of conventional water and wastewater treatment processes becomes increasingly challenged with the identification of more and more contaminants, rapid growth of population and industrial activities, and diminishing availability of water resources. Three emerging treatment technologies, including membrane filtration, advanced oxidation processes (AOPs), and UV irradiation, hold great promise to provide alternatives for better protection of public health and the environment and thus are reviewed in this paper. The emphasis was placed on their basic principles, main applications, and new developments. Advantages and disadvantages of these technologies are compared to highlight their current limitations and future research needs. It can be concluded that, along with the growing knowledge and the advances in manufacturing industry, the applications of these technologies will be increased at an unprecedented scale.Key words: water treatment, wastewater treatment, membrane filtration, ozonation, advanced oxidation processes, UV irradiation.

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 score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0010.002
Scholarly communication0.0010.002
Open science0.0010.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.003

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 head0.183
Teacher spread0.177 · 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

Citations114
Published2001
Admission routes1
Has abstractyes

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Same venueCanadian Journal of Civil EngineeringSame topicMembrane Separation TechnologiesFrench-language works237,207