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Record W2605713324 · doi:10.1504/ijenvh.2017.083974

Sampling of total mercury in sand on Sydney beaches and assessment of risk of exposure to children

2017· article· en· W2605713324 on OpenAlexaboutno aff
Katrina MacSween, Christina Y. Tang, Grant C. Edwards, Tingting Gan, S. Tran, S. Geremia, James Campbell, Dean Howard

Bibliographic record

VenueInternational Journal of Environment and Health · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicMercury impact and mitigation studies
Canadian institutionsnot available
Fundersnot available
KeywordsMercury (programming language)IngestionEnvironmental scienceEnvironmental chemistryMERCURY EXPOSUREHealth riskAnimal scienceChemistryBiomonitoringBiologyMedicineEnvironmental health

Abstract

fetched live from OpenAlex

Accumulation of anthropogenic mercury (Hg) onto coastal environments is potentially putting children playing in these areas, particularly beaches, at risk of exposure to mercury through the ingestion of sand. Samples were collected along 11 of Sydney's beaches and two Newcastle beaches where children may be exposed and analysed using a Direct Mercury Analyser (DMA-80). Risk of exposure was assessed based on Health Canada's exposure threshold for the ingestion of total mercury of 105ng Hg kg-1 BW d-1 and USEPA published values of daily ingestion rates by children (0.2g soil d-1 and 1.75g soil d-1). Concentrations of total mercury in beach sand ranged from 0.0035 to 57.89µg kg-1. Beaches with the highest Hg concentration were found to be located in close proximity to potential mercury sources. The highest daily intake calculated was 7.132ng Hg kg-1 BW d-1, well below the daily intake threshold, indicating children have a minimal exposure risk.

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)0.001
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 score0.047
Threshold uncertainty score0.094

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 science0.0000.000
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 head0.042
GPT teacher head0.358
Teacher spread0.317 · 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

Citations2
Published2017
Admission routes1
Has abstractyes

Explore more

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