{"id":"W2577808145","doi":"10.1016/j.ijheh.2017.01.001","title":"Univariate predictors of maternal concentrations of environmental chemicals: The MIREC study","year":2017,"lang":"en","type":"article","venue":"International Journal of Hygiene and Environmental Health","topic":"Effects and risks of endocrine disrupting chemicals","field":"Environmental Science","cited_by":55,"is_retracted":false,"has_abstract":true,"ca_institutions":"Health Canada; Université de Montréal; Centre Hospitalier Universitaire de Sherbrooke; Université de Sherbrooke","funders":"National Institute on Minority Health and Health Disparities; Canadian Institutes of Health Research; Health Canada","keywords":"Univariate; Environmental health; Univariate analysis; Environmental medicine; Medicine; Environmental science; Toxicology; Environmental chemistry; Internal medicine; Statistics; Chemistry; Biology; Multivariate analysis; Public health; Multivariate statistics; Mathematics; Pathology","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":[0.0008071605,0.0002857143,0.0002871598,0.0005129412,0.0004133807,0.0005925219,0.0006551323,0.0004334416,0.001382226],"category_scores_gemma":[0.002866368,0.0002657877,0.0004667072,0.001120087,0.0002282591,0.0002943526,0.0006025565,0.0006902013,0.0001888974],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007435562,"about_ca_system_score_gemma":0.001131273,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1152259,"about_ca_topic_score_gemma":0.1203932,"domain_scores_codex":[0.9993896,0.0001527112,0.00004231108,0.000159998,0.0001287849,0.0001265949],"domain_scores_gemma":[0.9983797,0.0002919066,0.0006276505,0.000177466,0.0002532943,0.0002699422],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00005682058,0.00000878609,0.9993783,0.000003792095,0.000030848,0.00003871853,0.0000285581,0.00001438621,0.00005227523,0.00001290976,0.0001075054,0.0002670328],"study_design_scores_gemma":[0.000004523632,0.00002708124,0.9992631,0.000008056529,0.00003353821,0.00009135579,0.0001194538,0.0001579263,0.00003384296,0.00001125114,0.000247478,0.000002294383],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9974329,0.000457352,0.0000900772,0.0001177696,0.000006806296,0.000008584278,0.001312724,0.000004711128,0.0005690551],"genre_scores_gemma":[0.9984044,0.0002083105,0.0001342264,0.00003582459,0.000005763535,0.00001117272,0.0009549135,0.000004041887,0.000241409],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1152259,"threshold_uncertainty_score":0.2291104,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01013574890191926,"score_gpt":0.3292791350844358,"score_spread":0.3191433861825166,"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."}}