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Record W2043269434 · doi:10.1021/es2045585

Pb Particles from Tap Water: Bioaccessibility and Contribution to Child Exposure

2012· article· en· W2043269434 on OpenAlexaff
Elise Deshommes, Michèle Prévost

Bibliographic record

VenueEnvironmental Science & Technology · 2012
Typearticle
Languageen
FieldEnvironmental Science
TopicHeavy Metal Exposure and Toxicity
Canadian institutionsPolytechnique MontréalNatural Sciences and Engineering Research Council of Canada
Fundersnot available
KeywordsTap waterEnvironmental scienceEnvironmental chemistryEnvironmental healthEnvironmental engineeringChemistryMedicine

Abstract

fetched live from OpenAlex

High particulate lead (Pb) levels can be measured in tap water, but the hazard linked to particulate Pb ingestion is unknown. An in vitro test was developed to determine the bioaccessibility of Pb particles from tap water, based on the Relative Bioaccessibility Leaching Procedure validated for soils, and applied to lab-generated particles and field particles collected behind the aerator tap. Field particles were found in 43% of the 342 taps investigated equipped with an aerator, and contained significant amounts of Pb (0.003-71%, median 4.7%). The bioaccessibility of lab-generated particles ranged from 2 to 96% depending on the particle type (Pb(II) > Brass > Pb(IV) > solder), while that of field particles was distributed between 1.5 and 100% (median 41%). The hazard of particulate Pb ingestion depends on the amount and concentration ingested, and the bioaccessibility of the particulate Pb forms involved. Using the Integrated Exposure Uptake Biokinetic model, the impact of particulate Pb on the exposure of children aged 0.5-7 for the distribution system studied was the most significant when considering a fraction of the exposure from large buildings.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0000.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.005
GPT teacher head0.217
Teacher spread0.211 · 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; both teacher heads agree on what is shown here.

Study designBench or experimental
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

Citations42
Published2012
Admission routes1
Has abstractyes

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