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Record W2301546665 · doi:10.2166/wst.2015.481

Removal of endocrine disrupting compounds from wastewater using polymer particles

2015· article· en· W2301546665 on OpenAlexafffund
Audrey Murray, Banu Örmeci, Edward P. C. Lai

Bibliographic record

VenueWater Science & Technology · 2015
Typearticle
Languageen
FieldChemistry
TopicAnalytical chemistry methods development
Canadian institutionsCarleton University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsNIPBisphenol AWastewaterChemistryAdsorptionEnvironmental chemistryOrganic matterPulp and paper industryWaste managementEnvironmental scienceOrganic chemistryEnvironmental engineeringMaterials scienceEpoxyComposite material

Abstract

fetched live from OpenAlex

This study evaluated the use of particles of molecularly imprinted and non-imprinted polymers (MIP and NIP) as a wastewater treatment method for endocrine disrupting compounds (EDCs). MIP and NIP remove EDCs through adsorption and therefore do not result in the formation of partially degraded products. The results show that both MIP and NIP particles are effective for removal of EDCs, and NIP have the advantage of not being as compound-specific as the MIP and hence can remove a diverse range of compounds including 17-β-estradiol (E2), atrazine, bisphenol A, and diethylstilbestrol. Removal of E2 from wastewater was also tested to determine the effectiveness of NIP in the presence of interfering substances and natural organic matter. Removal of E2 from wastewater samples was high and increased with increasing NIP. NIP represent an effective way of removing a wide variety of EDCs from wastewater.

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)0.000
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.077
Threshold uncertainty score0.566

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.053
GPT teacher head0.313
Teacher spread0.260 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations4
Published2015
Admission routes2
Has abstractyes

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