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Mixing behaviour and sources of Ag, Pd, and other trace elements in the Estuary and Gulf of St. Lawrence under winter conditions

2024· article· en· W4400900137 on OpenAlexafffund
Duc Huy Dang, Wei Wang, Dario Omanović, Alfonso Mucci

Bibliographic record

VenueChemosphere · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicHeavy metals in environment
Canadian institutionsMcGill UniversityTrent University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsEstuaryMixing (physics)TRACE (psycholinguistics)OceanographyEnvironmental scienceEnvironmental chemistryAtmospheric sciencesHydrology (agriculture)GeologyChemistryPhysicsGeotechnical engineering

Abstract

fetched live from OpenAlex

The marine chemistry of platinum group elements is poorly documented despite robust evidence of their widespread emissions and deposition around the globe. Here, we report the concentrations and discuss the geochemical behaviours of Ag, Pd and other trace and ultra-trace elements in the Estuary and Gulf of St. Lawrence (EGSL). We highlight the contrasting mixing behaviours of these elements, i.e., conservative (Cd, Re) vs. non-conservative (Ag, Pd), in samples collected during the winter and under ice-covered conditions. We ascribe the contrasting geochemical behaviour of these elements to their differential affinity for reactive surfaces carried into the estuary from the frozen watersheds. We also report an increase of the concentrations of Ag (up to 40 pmol L−1), Pd (up to 10 pmol L−1) and Pt (up to 0.4 pmol L−1) in the bottom and oxygen-depleted waters of the Gulf of St. Lawrence (GSL). A strong correlation between dissolved Pt concentrations and the stable carbon isotopic composition of the dissolved inorganic carbon (δ13C-DIC) suggests that the increased mobility of Pt may result from the aerobic mineralization of organic carbon or the oxidation of Pt-bearing organic complexes. Molar Pt/Pd ratios in the three water masses that compose the water column in the EGSL highlight a potential influence of anthropogenic sources near urban centers. The signature of continental end-members will be required to confirm the impacts of road traffic on the estuarine geochemistry of these elements.

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 score0.900
Threshold uncertainty score0.199

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 communication0.0010.000
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 head0.015
GPT teacher head0.259
Teacher spread0.244 · 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

Citations4
Published2024
Admission routes2
Has abstractyes

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