{"id":"W2795300584","doi":"10.1136/bmjopen-2017-018324","title":"GCAT|Genomes for life: a prospective cohort study of the genomes of Catalonia","year":2018,"lang":"en","type":"article","venue":"BMJ Open","topic":"Nutrition, Genetics, and Disease","field":"Biochemistry, Genetics and Molecular Biology","cited_by":74,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Barcelona Supercomputing Center; Agència de Gestió d'Ajuts Universitaris i de Recerca; Ministerio de Economía y Competitividad; Generalitat de Catalunya; Departament d'Universitats, Recerca i Societat de la Informació; Instituto de Salud Carlos III; McGill University Health Centre; Centres de Recerca de Catalunya; McGill University","keywords":"Medicine; Overweight; Epidemiology; Cohort; Anthropometry; Prospective cohort study; Cohort study; Public health; Body mass index; European Prospective Investigation into Cancer and Nutrition; Gerontology; Environmental health; Demography; Internal medicine; Pathology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002257416,0.001011028,0.0007093975,0.001064175,0.001606331,0.001697106,0.001316457,0.001090302,0.004352648],"category_scores_gemma":[0.002902751,0.0006675056,0.0008657253,0.001792141,0.0003224934,0.0004849644,0.001530425,0.001256207,0.002027046],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002409172,"about_ca_system_score_gemma":0.002106506,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1291577,"about_ca_topic_score_gemma":0.09866188,"domain_scores_codex":[0.998381,0.0005554036,0.0001218287,0.0004796537,0.0002233203,0.0002387962],"domain_scores_gemma":[0.9978954,0.0001695917,0.0003792115,0.0003953555,0.0006610738,0.0004994237],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002820886,0.0005607764,0.9412475,0.0003637801,0.0008063667,0.0009347654,0.001172865,0.000381425,0.001540014,0.0003731232,0.03794359,0.01185482],"study_design_scores_gemma":[0.0004217686,0.0002847071,0.9864416,0.0001681877,0.0001694819,0.0003702386,0.0006368422,0.000282425,0.00007958796,0.0001017212,0.01101159,0.00003181144],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8743466,0.002233157,0.001172476,0.001199735,0.0003024756,0.001136019,0.1147685,0.0001008871,0.004740041],"genre_scores_gemma":[0.8914322,0.001401288,0.003882567,0.00197295,0.0002743234,0.002255147,0.09104703,0.0001255562,0.007609012],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1291577,"threshold_uncertainty_score":0.2568119,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02760064086510767,"score_gpt":0.3511551592003117,"score_spread":0.323554518335204,"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."}}