{"id":"W824636173","doi":"10.1016/j.envres.2015.06.020","title":"Tea consumption in pregnancy as a predictor of pesticide exposure and adverse birth outcomes: The MIREC Study","year":2015,"lang":"en","type":"article","venue":"Environmental Research","topic":"Tea Polyphenols and Effects","field":"Medicine","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa; Health Canada; Université de Sherbrooke","funders":"Canadian Institutes of Health Research; Health Canada; Public Health Agency of Canada; Health Research Board","keywords":"Pesticide; Pregnancy; Environmental health; Consumption (sociology); Adverse effect; Toxicology; Medicine; Obstetrics; Biology; Internal medicine; Ecology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001482296,0.0003041995,0.0004225443,0.0004886783,0.0004177449,0.0005579346,0.0006165583,0.0005451241,0.001047976],"category_scores_gemma":[0.002809271,0.0003139722,0.0005753948,0.001169207,0.0002126352,0.0003376136,0.0006045204,0.0006813535,0.0001481666],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000534018,"about_ca_system_score_gemma":0.0007642843,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04757868,"about_ca_topic_score_gemma":0.0555655,"domain_scores_codex":[0.9992408,0.0002912287,0.00005686441,0.0001789898,0.0001414718,0.00009073874],"domain_scores_gemma":[0.9984682,0.0002972591,0.00064711,0.0002019247,0.0001831256,0.0002022549],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006827514,0.0000333873,0.9972647,0.00003866248,0.0002280772,0.00008260268,0.00009025805,0.00003460227,0.0002091442,0.00002833694,0.0002491102,0.001058433],"study_design_scores_gemma":[0.00003602921,0.000112095,0.9987816,0.0000277919,0.0001377575,0.0001551983,0.000089584,0.0001516782,0.00005074415,0.00001310172,0.0004403134,0.000004186081],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.994857,0.002160472,0.0001560043,0.0001945958,0.00001023404,0.00002178888,0.001878348,0.000005579563,0.0007160113],"genre_scores_gemma":[0.9973006,0.0007739872,0.0002663425,0.00007532959,0.00001500648,0.00003529072,0.0011841,0.000004722732,0.0003448133],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04757868,"threshold_uncertainty_score":0.09460348,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07343392529494205,"score_gpt":0.3652256276264815,"score_spread":0.2917917023315395,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}