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Record W4376958651 · doi:10.1080/22423982.2023.2208810

Sources of exposure to lead in Arctic and subarctic regions: a scoping review

2023· review· en· W4376958651 on OpenAlexafffundabout
Jordyn A. Stalwick, Mylène Ratelle, Kirsty E. B. Gurney, Mallory Drysdale, C. Lăzărescu, Jérôme Comte, Brian Laird, Kelly Skinner

Bibliographic record

VenueInternational Journal of Circumpolar Health · 2023
Typereview
Languageen
FieldSocial Sciences
TopicEnvironmental Justice and Health Disparities
Canadian institutionsGDG EnvironnementInstitut National de la Recherche ScientifiqueUniversity of WaterlooEnvironment and Climate Change Canada
FundersCrown-Indigenous Relations and Northern Affairs Canada
KeywordsSubarctic climateLead (geology)ArcticIndigenousCircumpolar starThe arcticGeographyLead exposureEnvironmental scienceEnvironmental healthEnvironmental protectionEcologyPhysical geographyOceanographyMedicineBiologyArchaeologyGeology

Abstract

fetched live from OpenAlex

Understanding lead exposure pathways is a priority because of its ubiquitous presence in the environment as well as the potential health risks. We aimed to identify potential lead sources and pathways of lead exposure, including long-range transport, and the magnitude of exposure in Arctic and subarctic communities. A scoping review strategy and screening approach was used to search literature from January 2000 to December 2020. A total of 228 academic and grey literature references were synthesised. The majority of these studies (54%) were from Canada. Indigenous people in Arctic and subarctic communities in Canada had higher levels of lead than the rest of Canada. The majority of studies in all Arctic countries reported at least some individuals above the level of concern. Lead levels were influenced by a number of factors including using lead ammunition to harvest traditional food and living in close proximity to mines. Lead levels in water, soil, and sediment were generally low. Literature showed the possibility of long-range transport via migratory birds. Household lead sources included lead-based paint, dust, or tap water. This literature review will help to inform management strategies for communities, researchers, and governments, with the aim of decreasing lead exposure in northern regions.

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)0.003
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.365
Threshold uncertainty score0.622

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.127
GPT teacher head0.464
Teacher spread0.337 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreReview

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

Citations12
Published2023
Admission routes3
Has abstractyes

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