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Record W1991722763 · doi:10.1021/es702449c

Mutagenic and Carcinogenic Hazards of Settled House Dust I: Polycyclic Aromatic Hydrocarbon Content and Excess Lifetime Cancer Risk from Preschool Exposure

2008· article· en· W1991722763 on OpenAlexaff
Rebecca M. Maertens, Xiaofeng Yang, Jiping Zhu, Rémi Gagné, George R. Douglas, Paul A. White

Bibliographic record

VenueEnvironmental Science & Technology · 2008
Typearticle
Languageen
FieldEnvironmental Science
TopicToxic Organic Pollutants Impact
Canadian institutionsHealth Canada
FundersNational Cancer Institute
KeywordsEnvironmental chemistryPolycyclic aromatic hydrocarbonEnvironmental scienceCarcinogenHydrocarbonEnvironmental healthChemistryToxicologyMedicineOrganic chemistryBiology

Abstract

fetched live from OpenAlex

Settled house dust (SHD) may be a significant source of children's indoor exposure to hazardous substances including polycyclic aromatic hydrocarbons (PAHs). In this study, organic extracts of sieved vacuum cleaner dust from 51 homes were examined for the presence of 13 PAHs via GC/MS. PAHs were found in all samples with levels of total PAHs ranging between 1.5 and 325 microg g(-1). The PAH concentrations in the SHD were correlated with information contained in corresponding household questionnaires. Analyses showed levels of PAHs to be negatively associated with noncombustion activities such as vacuum cleaning frequency. A risk assessment was conducted to evaluate the excess lifetime cancer risks posed to preschool aged children who ingested PAHs in SHD. The assessment revealed that exposure to PAHs at levels found in 90% of the homes (< 40 microg g(-1)) would result in excess cancer risks that are considered acceptable (i.e., 1-100 x 10(-6)). However, exposure to higher levels of PAHs found in five homes yielded risks that could be higher than 1 x 10(-4).

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)0.000
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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.008
GPT teacher head0.202
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 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

Citations161
Published2008
Admission routes1
Has abstractyes

Explore more

Same venueEnvironmental Science & TechnologySame topicToxic Organic Pollutants ImpactFrench-language works237,207