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Record W3203268499 · doi:10.1002/etc.5228

Trace Metal Residues in Marine Mussels: A Global Survey

2021· article· en· W3203268499 on OpenAlexafffund
Maximiliano Cledón, Louis A. Tremblay, Charles L. Griffiths, Mariem Fadhlaoui, Olivier Champeau, Marina Albentosa, V. Besada, Victor H. Fernandez, Christopher W. McKindsey, Leah Bendell, Bin Zhang, Zaúl García-Esquivel, Sergio Curiel-Ramı́rez, Satinder Kaur Brar, Pratik Kumar, Olivier Laroche, Patrice Couture

Bibliographic record

VenueEnvironmental Toxicology and Chemistry · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental Toxicology and Ecotoxicology
Canadian institutionsSimon Fraser UniversityYork UniversityUniversité du Québec à RimouskiFisheries and Oceans CanadaInstitut National de la Recherche Scientifique
FundersNatural Sciences and Engineering Research Council of CanadaUniversidad Autónoma de Baja CaliforniaUniversity of Cape Town
KeywordsBiomonitoringBiotaEnvironmental chemistryEnvironmental scienceMytilusCadmiumMercury (programming language)Trace metalPollutantBioaccumulationEcologyChemistryBiologyMetal

Abstract

fetched live from OpenAlex

Pressures from anthropogenic activities are causing degradation of estuarine and coastal ecosystems around the world. Trace metals are key pollutants that are released and can partition in a range of environmental compartments, to be ultimately accumulated in exposed biota. The level of pressure varies with locations and the range and intensity of anthropogenic activities. The present study measured residues of trace metals in Mytilus mussel species collected from a range of locations around the world in areas experiencing a gradient of anthropogenic pressures that we classified as low, moderate, or high impact. The data showed no grouping/impact level when sampling sites in all countries were incorporated in the analysis, but there was significant clustering/impact level for most countries. Overall, high-impact areas were characterized by elevated concentrations of zinc, lead, nickel, and arsenic, whereas copper and silver were detected at higher concentrations in medium-impact areas. Finally, whereas most metals were found at lower concentrations in areas classified as low impact, cadmium was typically elevated in these areas. The present study provides a unique snapshot of worldwide levels of coastal metal contamination through the use of Mytilus species, a well-established marine biomonitoring tool. Environ Toxicol Chem 2021;40:3434-3440. © 2021 SETAC.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.009
GPT teacher head0.221
Teacher spread0.212 · 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 designObservational
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

Citations6
Published2021
Admission routes2
Has abstractyes

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