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Record W2414187066 · doi:10.2166/wst.2016.270

Sorption and toxicity reduction of pharmaceutically active compounds and endocrine disrupting chemicals in the presence of colloidal humic acid

2016· article· en· W2414187066 on OpenAlexfundno aff
Injeong Kim, Hyo-Dong Kim, Tae‐Yong Jeong, Sang Don Kim

Bibliographic record

VenueWater Science & Technology · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicPharmaceutical and Antibiotic Environmental Impacts
Canadian institutionsnot available
FundersMinistry of Science, ICT and Future PlanningPublic Health Agency of Canada
KeywordsSorptionChemistryEnvironmental chemistryHumic acidToxicityBioassayBioavailabilityChromatographyAtrazineAdsorptionOrganic chemistryBiologyPesticidePharmacologyEcology

Abstract

fetched live from OpenAlex

This study investigated the toxicity changes and sorption of pharmaceuticals and endocrine disrupters in the presence of humic acid (HA). For the sorption experiment, a dead end filtration (DEF) system was used to separate bound and free-form target compounds. An algae growth inhibition test and E-screen assay were conducted to estimate the toxic effect of pharmaceutically active compounds (PhACs) and endocrine disrupting chemicals (EDCs), respectively. The permeate concentration was confirmed using liquid chromatography-mass spectrometry. In the sorption test, we observed significant sorption of PhACs and EDCs on colloidal HA, except for sulfamethoxazole (SMX). The values of log KCOC derived from DEF determinations ranged from 4.40 to 5.03. The removal efficiency varied with the HA concentration and the target chemical properties. Tetracycline and 4-octylphenol showed the highest sorption or removal efficiency (≈50%), even at 5 mg C/L HA. The algal growth inhibition of PhACs and the estrogenic effects of EDCs were significantly decreased in proportion to HA concentrations, except for SMX. In addition, the chemical analysis results showed a positive relationship with the bioassay results. Consequently, the sorption of PhACs and EDCs onto colloidal HA should be emphasized in natural environments because it significantly reduces bioavailable concentrations and toxicity to aquatic organisms.

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 categoriesScience and technology studies
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 score0.009
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.005
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.017
GPT teacher head0.292
Teacher spread0.275 · 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.

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

Citations10
Published2016
Admission routes1
Has abstractyes

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