{"id":"W2416272036","doi":"10.1136/jmedgenet-2015-103578.28","title":"MG-129 Our experience of<i>in silico</i>gene panel testing for clinically heterogeneous disorders using exome sequencing","year":2015,"lang":"en","type":"article","venue":"Journal of Medical Genetics","topic":"Genomics and Rare Diseases","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Hospital for Sick Children","funders":"","keywords":"Exome sequencing; Sanger sequencing; Genetics; Exome; DNA sequencing; Indel; Bioinformatics; Computational biology; Medicine; Biology; Gene; Single-nucleotide polymorphism; Mutation; Genotype","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008872105,0.0001419793,0.0003029888,0.00006293916,0.00003154344,0.00001541713,0.0004200241,0.0002116503,0.000002108715],"category_scores_gemma":[0.00215251,0.0001230564,0.0001763133,0.00009825418,0.00008184831,0.000003655969,0.0001301763,0.000139351,2.876044e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003490937,"about_ca_system_score_gemma":0.0009095736,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001541117,"about_ca_topic_score_gemma":0.00001417501,"domain_scores_codex":[0.9980621,0.00007166229,0.0008911147,0.0001984001,0.0005068005,0.0002699504],"domain_scores_gemma":[0.9985666,0.00005814675,0.0004473611,0.0001935032,0.0003159848,0.0004184419],"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":[0.0004976543,0.0004270007,0.06089415,0.0001045426,0.0001206976,0.000185364,0.000744073,0.03243678,0.8827376,0.000004548524,0.0001924416,0.02165508],"study_design_scores_gemma":[0.03639679,0.02677179,0.02429106,0.002305629,0.0009626213,0.008962401,0.02736847,0.17841,0.6689894,0.004463033,0.01694879,0.004130051],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9909368,0.002873537,0.005500379,0.0001440456,0.0004022783,0.0001165247,0.00001160534,0.000001918369,0.00001289493],"genre_scores_gemma":[0.9818517,0.0005157568,0.01687325,0.0002197819,0.0005006944,0.000002943984,0.000005167856,0.00002332251,0.000007382293],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2137483,"threshold_uncertainty_score":0.5018094,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1108650225422151,"score_gpt":0.3619732819123574,"score_spread":0.2511082593701423,"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."}}