MétaCan
Menu
Back to cohort
Record W2500896792 · doi:10.2136/sssabookser10.c43

Methods for Determining Emerging Contaminants in Wetland Matrices

2013· book-chapter· en· W2500896792 on OpenAlexaff
Jeremy L. Conkle, John R. White, Chris D. Metcalfe

Bibliographic record

VenueSoil Science Society of America book series · 2013
Typebook-chapter
Languageen
FieldEnvironmental Science
TopicPharmaceutical and Antibiotic Environmental Impacts
Canadian institutionsTrent University
Fundersnot available
KeywordsWastewaterWetlandContaminationExtraction (chemistry)Environmental scienceEnvironmental chemistryIsotope dilutionAquatic ecosystemChemistryEnvironmental engineeringMass spectrometryChromatographyEcologyBiology

Abstract

fetched live from OpenAlex

Emerging contaminants are a growing concern in the environment. While their impact to humans is probably minimal, the main concern is their effect on aquatic organisms. These compounds enter aquatic ecosystems from agricultural runoff and treated wastewater discharge. Currently, regulations do not account for these compounds in wastewater treatment systems, which degrade and sequester compounds to varying degrees before discharge. Recent research has demonstrated the ability of wastewater treatment wetlands to reduce the loading of emerging contaminants into downstream water bodies. This chapter examines published extraction and analytical methods as well as USEPA Method 1694 to detect emerging contaminants in wetland environments. The extraction of compounds from low and high organic matter soils is discussed, followed by procedures to further remove interferences from soil extract and water samples with solid-phase extraction. The isotope dilution method, which incorporates deuterated standards for each analyte of interest, is used to assess compound recovery, correct for matrix effects and account for instrument sensitivity. Equations are presented to properly calculate compound concentrations using deuterated standards. The samples generated using these methods are best analyzed with a high-performance liquid chromatography tandem mass spectrometer (HPLC-MS/MS). Finally, a recent study utilizing an adapted version of this method is presented to demonstrate a potential application with wetland samples.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.891
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.005
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.000
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 head0.026
GPT teacher head0.327
Teacher spread0.301 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueSoil Science Society of America book seriesSame topicPharmaceutical and Antibiotic Environmental ImpactsFrench-language works237,207