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Farm Childrenʼs Exposure to Herbicides

2004· article· en· W2075406430 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueEpidemiology · 2004
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPesticide Exposure and Toxicity
Canadian institutionsUniversity of GuelphUniversity of TorontoHealth Canada
FundersDivision of Environmental Biology
KeywordsMCPABiomonitoringPesticideUrineToxicology2,4-Dichlorophenoxyacetic acidGold standard (test)Exposure assessmentEnvironmental healthMedicineAnimal scienceBiologyEnvironmental chemistryChemistryAgronomyInternal medicineEcology

Abstract

fetched live from OpenAlex

BACKGROUND: Pesticide exposure has been associated with various childhood cancers. However, most studies rely on questionnaires, with few using biologic measures of dose. This study was designed to measure herbicide exposure directly in children of farm applicators, and to compare these results with exposure imputed from questionnaire information. METHODS: Two consecutive 24-hour urine samples were collected from 92 children of Ontario farm applicators who used the herbicides 2,4-D (2,4-dichlorophenoxyacetic acid) or MCPA (4-chloro-2-methylphenoxyacetic acid) for the first time during 1996. The farm applicator completed questionnaires describing his pesticide-handling practices as well as the child's location during the various stages of handling these pesticides. RESULTS: Approximately 30% of the children on farms using these herbicides had detectable concentrations in their urine, with maximum values of 100 microg/L for 2,4-D and 45 microg/L for MCPA. Children with higher levels were more likely to be boys and to have parents who also had higher mean urinary concentrations. The sensitivity and specificity of a simple indicator of use were 47% and 72%, respectively, for 2,4-D, and 91% and 30%, respectively, for MCPA, using the biomonitoring data as the gold standard. CONCLUSIONS: Information on living on a farm, or on living on a farm where a specific pesticide is used, is not enough to classify children's exposures. Given this potential for misclassification, we urge incorporation of biomonitoring studies in subsets of children at least to estimate the extent of misclassification.

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.

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)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.535
Threshold uncertainty score0.570

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.040
GPT teacher head0.274
Teacher spread0.234 · 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