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Record W1981504249 · doi:10.1289/ehp.7985

History of Inuit Community Exposure to Lead, Cadmium, and Mercury in Sewage Lake Sediments

2005· article· en· W1981504249 on OpenAlexaboutno aff
Mark H. Hermanson, James R. Brozowski

Bibliographic record

VenueEnvironmental Health Perspectives · 2005
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsnot available
Fundersnot available
KeywordsMercury (programming language)SewageEnvironmental scienceCadmiumArcticEnvironmental chemistryPopulationSedimentIngestionEnvironmental engineeringEcologyChemistryBiologyEnvironmental health

Abstract

fetched live from OpenAlex

Exposure to lead, cadmium, and mercury is known to be high in many arctic Inuit communities. These metals are emitted from industrial and urban sources, are distributed by long-range atmospheric transport to remote regions, and are found in Inuit country foods. Current community exposure to these metals can be measured in food, but feces and urine are also excellent indicators of total exposure from ingestion and inhalation because a high percentage of each metal is excreted. Bulk domestic sewage or its residue in a waste treatment system is a good substitute measure. Domestic waste treatment systems that accumulate metals in sediment provide an accurate historical record of changes in ingestion or inhalation. We collected sediment cores from an arctic lake used for facultative domestic sewage treatment to identify the history of community exposure to Pb, Cd, and Hg. Cores were dated and fluxes were measured for each metal. A nearby lake was sampled to measure combined background and atmospheric inputs, which were subtracted from sewage lake data. Pb, Cd, and Hg inputs from sewage grew rapidly after the onset of waste disposal in the late 1960s and exceeded the rate of population growth in the contributing community from 1970 to 1990. The daily per-person Pb input in 1990 (720,000 ng/person per day) exceeded the tolerable daily intake level. The Cd input (48,000 ng/person per day) and Hg input (19,000 ng/person per day) were below the respective TDI levels at the time.

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 score0.738
Threshold uncertainty score0.522

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 studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
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 head0.032
GPT teacher head0.341
Teacher spread0.310 · 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

Citations14
Published2005
Admission routes1
Has abstractyes

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