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Record W2091540618 · doi:10.1021/es702448x

Mutagenic and Carcinogenic Hazards of Settled House Dust II: Salmonella Mutagenicity

2008· article· en· W2091540618 on OpenAlexafffund
Rebecca M. Maertens, Rémi Gagné, George R. Douglas, Jiping Zhu, Paul A. White

Bibliographic record

VenueEnvironmental Science & Technology · 2008
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCarcinogens and Genotoxicity Assessment
Canadian institutionsHealth Canada
FundersHealth CanadaNational Institutes of Health
KeywordsSalmonellaCarcinogenEnvironmental scienceEnvironmental chemistryEnvironmental healthToxicologyChemistryBiologyBacteriaMedicineGenetics

Abstract

fetched live from OpenAlex

Settled house dust (SHD) is a complex mixture that contains numerous chemical contaminants. Very little is known about the hazards of SHD as compared to other complex matrices such as air and soil. In this study, the mutagenic hazards associated with the extracts of sieved dust from 52 homes were examined using the Salmonella Mutagenicity Test. All of the SHD samples displayed mutagenic activity and the mean mutagenic potencies ranged from 2300to 23 600 revertants per gram. Testing with various Salmonella strains revealed a predominance of frameshift mutagens in the dust samples. Analyses showed that polycyclic aromatic hydrocarbons (PAHs) were likely responsible for a quarter of the mutagenic activity of the SHD samples. In an effort to identify factors that influenced dust mutagenicity, the relationships between SHD mutagenicity and household activities were investigated. Mutagenicity was positively correlated with parameters such as the time since last vacuuming (r2 = 0.11, p < 0.05) and the number of people living in the home (r2 = 0.11-0.43, p < 0.05). However, the causative factors responsible for these relationships remain unclear.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
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 score0.033
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.003
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.006
GPT teacher head0.213
Teacher spread0.207 · 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.

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

Citations31
Published2008
Admission routes2
Has abstractyes

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