{"id":"W3096239322","doi":"10.1212/wnl.94.15_supplement.911","title":"RNAseq Analysis for The Diagnosis of Lissencephaly (911)","year":2020,"lang":"en","type":"article","venue":"Neurology","topic":"Genomics and Rare Diseases","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Hospital for Sick Children","funders":"","keywords":"Lissencephaly; Medicine; Library science; Biology; Computer science; Genetics","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":[],"consensus_categories":[],"category_scores_codex":[0.00139054,0.0006829154,0.0005493349,0.002413953,0.0005393195,0.0007242444,0.0005503291,0.001785282,0.004902953],"category_scores_gemma":[0.002713493,0.0002490539,0.0005554609,0.000673247,0.000721295,0.0003693244,0.0004385522,0.001000753,0.004158414],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005843156,"about_ca_system_score_gemma":0.0004714408,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009426258,"about_ca_topic_score_gemma":0.001040375,"domain_scores_codex":[0.9992736,0.0001194228,0.00008709735,0.0001644716,0.0002647042,0.00009068981],"domain_scores_gemma":[0.9989977,0.0003482818,0.0001026015,0.0001015279,0.0003082622,0.0001415318],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0008919062,0.0001289459,0.0979378,0.0004694588,0.00006469461,0.0315568,0.0003008595,0.0003805702,0.7898239,0.00153482,0.01308903,0.06382113],"study_design_scores_gemma":[0.0001006985,0.001097159,0.2402383,0.0003708739,0.000272385,0.1140317,0.0007910449,0.005025289,0.5319917,0.007190264,0.09878252,0.0001082446],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7851962,0.02111047,0.1122189,0.01647806,0.002417868,0.00072786,0.01658445,0.004732244,0.04053391],"genre_scores_gemma":[0.9017783,0.006653174,0.06688283,0.004026564,0.0004508121,0.0003249844,0.008336483,0.0004354246,0.01111134],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004902953,"threshold_uncertainty_score":0.01640201,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0173471585161607,"score_gpt":0.247466661196598,"score_spread":0.2301195026804373,"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."}}