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Record W1777176533 · doi:10.1002/ieam.1502

Passive sampling methods for contaminated sediments: State of the science for metals

2013· review· en· W1777176533 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueIntegrated Environmental Assessment and Management · 2013
Typereview
Languageen
FieldEnvironmental Science
TopicHeavy metals in environment
Canadian institutionsInstitut National de la Recherche Scientifique
FundersStrategic Environmental Research and Development ProgramSociety of Environmental Toxicology and ChemistryU.S. Department of Defense
KeywordsEnvironmental scienceContaminationSampling (signal processing)MetalloidSedimentBioaccumulationEnvironmental chemistryPassive samplingBiotaBiochemical engineeringComputer scienceChemistryGeologyEcologyEngineeringMetal

Abstract

fetched live from OpenAlex

Abstract “Dissolved” concentrations of contaminants in sediment porewater (Cfree) provide a more relevant exposure metric for risk assessment than do total concentrations. Passive sampling methods (PSMs) for estimating Cfree offer the potential for cost-efficient and accurate in situ characterization of Cfree for inorganic sediment contaminants. In contrast to the PSMs validated and applied for organic contaminants, the various passive sampling devices developed for metals, metalloids, and some nonmetals (collectively termed “metals”) have been exploited to a limited extent, despite recognized advantages that include low detection limits, detection of time-averaged trends, high spatial resolution, information about dissolved metal speciation, and the ability to capture episodic events and cyclic changes that may be missed by occasional grab sampling. We summarize the PSM approaches for assessing metal toxicity to, and bioaccumulation by, sediment-dwelling biota, including the recognized advantages and limitations of each approach, the need for standardization, and further work needed to facilitate broader acceptance and application of PSM-derived information by decision makers. Integr Environ Assess Manag 2014;10:179–196. © 2014 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals, Inc. on behalf of SETAC. Key Points Passive sampling methods (PSMs) offer the potential for cost-efficient and accurate in situ characterization of the dissolved concentrations for inorganic sediment contaminants. PSMs are useful for evaluating the geochemical behavior of metals in surficial sediments, including determination of fluxes across the sediment-water interface, and post-depositional changes in metal speciation. Few studies have tried to link PSM responses in sediments to metal uptake and toxicity responses in benthic organisms. There is a clear need for further studies. Future PSMs could be designed to mimic saturable kinetics, which would fill the gap between the kinetic and the equilibrium regime samplers currently used, and may improve prediction of metals accumulation by benthic 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.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.995
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0010.002
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 head0.057
GPT teacher head0.406
Teacher spread0.349 · 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