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Regional geochemical survey of Canadian Arctic sediments: insights into provenance, sediment dynamics and trace metal enrichment

2025· article· en· W4410478288 on OpenAlexafffundabout
Camille Brice, Jean‐Carlos Montero‐Serrano, Richard Saint‐Louis

Bibliographic record

VenueApplied Geochemistry · 2025
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeological Studies and Exploration
Canadian institutionsUniversité du Québec à Rimouski
FundersFonds de recherche du Québec – Nature et technologiesCanadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of CanadaArcticNetUniversidad Nacional Autónoma de MéxicoPolar Knowledge CanadaNatural Sciences and Engineering Research Council of CanadaUniversité du Québec à Montréal
KeywordsProvenanceSedimentGeologyArcticTrace metalTRACE (psycholinguistics)GeochemistryEarth scienceOceanographyGeomorphologyMetalChemistry

Abstract

fetched live from OpenAlex

Major and trace element content, grain size and total organic carbon content were measured in 141 marine surface and terrestrial sediment samples to study modern sediment dynamics in the Canadian Arctic (CA) and to provide an assessment of metals enrichment for V, Zn, Mn and Fe. Samples were collected from different areas between Baffin Bay and the Beaufort Sea during ArcticNet 2016-2022 expeditions onboard the Canadian Coast Guard icebreaker Amundsen. Geochemical data combined with multivariate statistical analyses allowed the division of the CA into three chemical clusters (CC) and four regional provinces. central CA (CC#1) and southeastern CA (CC#2) are mainly composed of relatively coarse sediments rich in detrital carbonates (Ca, Mg) and siliciclastic elements (Si, K, Zr), respectively, reflecting coastal erosion of surrounding land (e.g., Victoria Island, Baffin Island) and transport of sediment-laden sea ice. The sediments of CC#3, comprising western and eastern CA, are characterized by organic carbon and Fe-Mn oxyhydroxides. Western CA, which is also characterized by fine-grained aluminosilicates, is influenced by the Mackenzie River discharge, while eastern CA is shaped by polynyas and glacial erosion. The highest concentrations of V and Zn are recorded in the western CA. Over the whole region, significant positive correlations of Al with Zn, V and Fe suggest that lithogenic-derived inputs influence the distribution of these metals in sediments from the CA and that Fe oxides represent the main carrier phase. In western CA, Mn displays positive but weaker relationships with Al and Fe, suggesting a mixed source of Mn oxyhydroxides linked to both detrital fractions and authigenic processes near the sediment-water interface. High terrestrial Mn oxyhydroxide inputs from the Mackenzie River are remobilized and transported to areas with lower oxygen consumption in sediment, i.e., Amundsen Gulf and Banks Island coasts, which leads to surface sediment enrichment in Mn. The enrichment factor and the geo-accumulation index, two pollution indices commonly used for identifying anthropogenic metal inputs, were also studied to evaluate their suitability in the context of this study. Discrepancies from the normalization of metals with a geochemical background and a normalizing element revealed that pollution indices should be used with caution. Overall, according to the pollution indices and the regional survey, the surface sediments of the CA show minor enrichment in trace metals and thus present natural concentrations relative to regional background values.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.016
Threshold uncertainty score0.114

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0050.009
Science and technology studies0.0040.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.011
GPT teacher head0.197
Teacher spread0.186 · 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".

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Citations4
Published2025
Admission routes3
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