{"id":"W2563150189","doi":"10.1101/092346","title":"Mapping Autosomal Recessive Intellectual Disability: Combined Microarray and Exome Sequencing Identifies 26 Novel Candidate Genes in 192 Consanguineous Families","year":2016,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Genetics and Neurodevelopmental Disorders","field":"Biochemistry, Genetics and Molecular Biology","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University; Hospital for Sick Children; Fleming College; University of Toronto; Mount Sinai Hospital; Centre for Addiction and Mental Health","funders":"Tehran University of Medical Sciences and Health Services","keywords":"Genetics; Exome sequencing; Disease gene identification; Biology; Candidate gene; Exome; Consanguinity; Copy-number variation; Gene; Missense mutation; Genetic heterogeneity; Mutation; Genome; Phenotype","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000296862,0.0006125862,0.0005455894,0.0002025769,0.0001582467,0.0001674474,0.0004399412,0.0004786187,0.0000142671],"category_scores_gemma":[0.0003635517,0.0006118097,0.0001076457,0.0002222874,0.0005147959,0.00001160476,0.001015445,0.0003380928,0.000008008873],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001613845,"about_ca_system_score_gemma":0.0005097243,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000113109,"about_ca_topic_score_gemma":0.0001102066,"domain_scores_codex":[0.9971394,0.0001167077,0.0006215664,0.001318713,0.000211646,0.0005919499],"domain_scores_gemma":[0.9985355,0.00006147499,0.0002744532,0.0007594011,0.0001906505,0.0001784826],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0000683241,0.00007179509,0.01766618,0.0002612389,0.0001194062,0.00002051641,0.00008941517,0.00001778129,0.9815766,0.000007492912,0.00008369036,0.00001752795],"study_design_scores_gemma":[0.001091661,0.00009669764,0.1227934,0.0004177553,0.00003244389,2.973028e-7,0.000099604,0.00007816732,0.8727025,0.000005906605,0.001698652,0.0009828719],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9942462,0.003308888,0.0005827491,0.0001684563,0.0007524536,0.0005988652,0.0002540603,0.00007790075,0.00001042603],"genre_scores_gemma":[0.9956124,0.002770684,0.001084417,0.0001640223,0.00008997098,0.0001355143,0.000003430413,0.0001234585,0.00001606716],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1088741,"threshold_uncertainty_score":0.9996333,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0122863597814518,"score_gpt":0.2120305627141593,"score_spread":0.1997442029327075,"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."}}