MétaCan
Menu
Back to cohort
Record W2552782695 · doi:10.1097/jom.0000000000000875

Organophosphate Pesticide Urinary Metabolites Among Latino Immigrants

2016· article· en· W2552782695 on OpenAlexaff
Thomas A. Arcury, Paul J. Laurienti, Haiying Chen, Timothy D. Howard, Dana Boyd Barr, Dana C. Mora, Phillip Summers, Sara A. Quandt

Bibliographic record

VenueJournal of Occupational and Environmental Medicine · 2016
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPesticide Exposure and Toxicity
Canadian institutionsWind Energy Institute of Canada
FundersNational Institute of Environmental Health Sciences
KeywordsUrineCreatinineMetaboliteOrganophosphateUrinary systemPesticideMedicineEnvironmental healthImmigrationToxicologyInternal medicineGeographyBiologyAgronomy

Abstract

fetched live from OpenAlex

BACKGROUND: This analysis documents detections and concentrations of the six dialkylphosphate (DAP) urinary metabolite of organophosphorus (OP) pesticides among North Carolina Latino migrant farmworkers, with comparison to non-farmworker Latino immigrants. METHODS: Participants provided up to four urine samples during the 2012 and 2013 agricultural seasons. Composite urine samples for each year were analyzed. RESULTS: DAP urinary metabolite detections were similar in farmworkers and non-farmworker; for example, for 2012, 75.4% of farmworkers and 67.4% of non-farmworkers and, for 2013, 89.3% of farmworkers and 89.7% of non-farmworkers had dimethylthiophosphate detections. DAP geometric mean concentrations were high; for example, dimethylphosphate concentrations among farmworkers were 11.39 μg/g creatinine for 2012 and 4.49 μg/g creatinine for 2013, while they were 10.49 μg/g creatinine for 2012 and 1.97 μg/g creatinine for 2013 for non-farmworkers CONCLUSIONS:: Research to reduce pesticide exposure among Latino farmworkers and non-farmworkers is needed.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.297
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 studies0.0000.000
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 head0.016
GPT teacher head0.223
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 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

Citations34
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Occupational and Environmental MedicineSame topicPesticide Exposure and ToxicityFrench-language works237,207