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Record W6957898567 · doi:10.60692/kmjjf-48q85

Human health risk associated with metal exposure at Agbogbloshie e-waste site and the surrounding neighbourhood in Accra, Ghana

2023· article· en· W6957898567 on OpenAlexaff

Bibliographic record

VenueGreater South Information System · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicRecycling and Waste Management Techniques
Canadian institutionsRoyal Roads University
Fundersnot available
KeywordsHuman healthIngestionHealth riskRisk assessmentContaminationSoil PollutantsHeavy metals

Abstract

fetched live from OpenAlex

Agbogbloshie in Accra, Ghana, was a center for informal e-waste recycling until it was closed recently. This study investigated the potential health risks of toxic metals (including As, Cd, Cu, Ni, Pb, Sb, and Zn) found in the surface soils based on their concentrations and in vitro bioaccessibility. Mean concentrations at the burning sites were As: 218; Cd: 65; Cr: 182; Cu: 15,841; Ni: 145; Pb: 6,106; Sb: 552; and Zn: 16,065 mg/kg while the dismantling sites had mean concentrations of As: 23; Cd: 38; Cr: 342; Cu: 3239; Ni: 96; Pb: 681; Sb: 104; and Zn: 1658 mg/kg. The findings confirmed the enrichment of potentially toxic metals at the dismantling and burning sites, exceeding international environmental soil quality guidelines. Based on the total metal concentrations, bioaccessibility, and calculated risk indices, the risks associated with incidental ingestion of soil-borne metal contaminants at the dismantling and burning sites were very high. Despite evidence of higher metal concentrations in the communities near the burning and dismantling sites, the human health risk associated with soil ingestion was significantly lower in the surrounding neighborhood.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.023
Threshold uncertainty score0.418

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
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 head0.021
GPT teacher head0.216
Teacher spread0.194 · 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 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

Citations0
Published2023
Admission routes1
Has abstractyes

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