MétaCan
Menu
Back to cohort
Record W4211232695 · doi:10.1002/wer.1231

Physico‐chemical processes

2019· review· en· W4211232695 on OpenAlexaff
Weihang Ouyang, Tianhao Chen, Yihao Shi, Liangyu Tong, Yangyu Chen, Weiwen Wang, Jiajun Yang, Jinkai Xue

Bibliographic record

VenueWater Environment Research · 2019
Typereview
Languageen
FieldChemistry
TopicElectrochemical Analysis and Applications
Canadian institutionsUniversity of Regina
Fundersnot available
KeywordsEnvironmental science

Abstract

fetched live from OpenAlex

The review scans research articles published in 2018 on physico-chemical processes for water and wastewater treatment. The paper includes eight sections, that is, membrane technology, granular filtration, flotation, adsorption, coagulation/flocculation, capacitive deionization, ion exchange, and oxidation. The membrane technology section further divides into six parts, including microfiltration, ultrafiltration, nanofiltration, reverse osmosis/forward osmosis, and membrane distillation. PRACTITIONER POINTS: Totally 266 articles on water and wastewater treatment have been scanned; The review is sectioned into 8 major parts; Membrane technology has drawn the widest attention from the research community.

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)0.001
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 score0.008
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0080.007

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 head0.125
GPT teacher head0.388
Teacher spread0.263 · 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

Citations30
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueWater Environment ResearchSame topicElectrochemical Analysis and ApplicationsFrench-language works237,207