{"id":"W2896784358","doi":"10.1097/ede.0000000000000932","title":"Nonparticipation Selection Bias in the MOBI-Kids Study","year":2018,"lang":"en","type":"article","venue":"Epidemiology","topic":"Electromagnetic Fields and Biological Effects","field":"Biochemistry, Genetics and Molecular Biology","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ottawa Hospital; Children's Hospital of Eastern Ontario; University of Ottawa","funders":"National Cancer Institute; Departament de Salut, Generalitat de Catalunya; Agence Nationale de Sécurité Sanitaire de l’Alimentation, de l’Environnement et du Travail; Pfizer Foundation; Bundesamt für Strahlenschutz; Conselleria de Sanitat Universal i Salut Pública; Generalitat de Catalunya; Ministerio de Ciencia e Innovación; Ministry of Internal Affairs and Communications; Institut National Du Cancer; Generalitat Valenciana; Pfizer; European Commission; Centres de Recerca de Catalunya","keywords":"Selection bias; Medicine; Demography; Odds ratio; Odds; Selection (genetic algorithm); Logistic regression","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.06324267,0.000626857,0.0009239035,0.001783728,0.001185315,0.001161614,0.001544909,0.001002499,0.001144909],"category_scores_gemma":[0.09871271,0.0005904399,0.001198421,0.002288613,0.001295902,0.0008830946,0.0018612,0.0006526868,0.0002244134],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001009844,"about_ca_system_score_gemma":0.001647041,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008022092,"about_ca_topic_score_gemma":0.008273808,"domain_scores_codex":[0.8932453,0.08521965,0.007472174,0.004967912,0.006821865,0.002273098],"domain_scores_gemma":[0.9197689,0.03615957,0.02724268,0.01027651,0.005401496,0.001150855],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003795697,0.0000407359,0.9914523,0.0001896008,0.0004234542,0.000103955,0.002137711,0.00008494018,0.0001143951,0.0005388753,0.0006640374,0.003870405],"study_design_scores_gemma":[0.0001964505,0.0006605571,0.982551,0.0005398591,0.0007558021,0.000647072,0.002693687,0.001586657,0.0008332874,0.001296583,0.008201292,0.00003775037],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9756929,0.002943847,0.01316519,0.0007694688,0.0002003401,0.001594411,0.002415787,0.00003731246,0.0031809],"genre_scores_gemma":[0.9930289,0.0003147913,0.003240482,0.0004478568,0.00006247003,0.001467942,0.0009760105,0.00002105178,0.0004403581],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9367573,"threshold_uncertainty_score":0.3344631,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09057386185413108,"score_gpt":0.3795555400002615,"score_spread":0.2889816781461304,"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."}}