{"id":"W4220719918","doi":"10.1038/s41598-022-08938-y","title":"NeuroSCORE is a genome-wide omics-based model that identifies candidate disease genes of the central nervous system","year":2022,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Genomics and Rare Diseases","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Genome Canada","funders":"Bionano Genomics","keywords":"Genome; Computational biology; Disease; Gene; Candidate gene; Biology; Omics; Bioinformatics; Genetics; Medicine; Pathology","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":[0.002217573,0.00141903,0.0008224498,0.003946947,0.0005041533,0.001134669,0.0008310632,0.0005154796,0.005795082],"category_scores_gemma":[0.003197259,0.0002861545,0.001945225,0.002063209,0.0004118828,0.0004777011,0.001242315,0.0005639513,0.000913274],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007703042,"about_ca_system_score_gemma":0.001687849,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007292556,"about_ca_topic_score_gemma":0.0103914,"domain_scores_codex":[0.9990926,0.0002942461,0.00005882442,0.0002684871,0.0002302349,0.00005563863],"domain_scores_gemma":[0.9986595,0.0007016512,0.000238028,0.0001324061,0.000176413,0.00009199922],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.003774093,0.000579053,0.476077,0.002786421,0.005879791,0.00205861,0.0004930308,0.1742292,0.08228853,0.05234043,0.06185733,0.1376366],"study_design_scores_gemma":[0.0004520444,0.001052457,0.1090601,0.0002204195,0.0009400547,0.001739864,0.0002130464,0.7908314,0.01047978,0.03934827,0.04553253,0.0001301219],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2838461,0.00243915,0.5697862,0.003037222,0.0003347876,0.001271122,0.114199,0.01515351,0.009932907],"genre_scores_gemma":[0.6131384,0.001233244,0.3199425,0.00100266,0.0001064608,0.001734819,0.05876705,0.0007110361,0.003363815],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007292556,"threshold_uncertainty_score":0.01938653,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009727623893227648,"score_gpt":0.207720578546134,"score_spread":0.1979929546529063,"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."}}