{"id":"W3186454581","doi":"10.20944/preprints202107.0568.v1","title":"Genotype Pattern Mining for Pairs of Interacting Variants Underlying Digenic Traits","year":2021,"lang":"en","type":"preprint","venue":"Preprints.org","topic":"Genetic Associations and Epidemiology","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Japan Society for the Promotion of Science; Natural Sciences and Engineering Research Council of Canada","keywords":"Genetics; Biology; Genotype; Retinitis pigmentosa; Epistasis; Null (SQL); Phenotype; Gene; Computational biology; Evolutionary biology; Computer science; Data mining","routes":{"ca_aff":true,"ca_fund":true,"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":[0.003352285,0.0008682648,0.001201559,0.005648231,0.0005189607,0.00138561,0.001432415,0.001328373,0.003767174],"category_scores_gemma":[0.01462107,0.000382828,0.001977884,0.004010634,0.0003644158,0.0007465958,0.00141918,0.0008441878,0.001002482],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002680462,"about_ca_system_score_gemma":0.0008703807,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001416047,"about_ca_topic_score_gemma":0.002028001,"domain_scores_codex":[0.9959895,0.0008457734,0.0007072655,0.001706653,0.0005196687,0.0002311321],"domain_scores_gemma":[0.9868238,0.008850842,0.001584256,0.00170732,0.000662178,0.0003716011],"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":[0.002454996,0.0005412119,0.6412122,0.002415421,0.003163375,0.006747954,0.0005649276,0.01306535,0.02256225,0.004897462,0.01408747,0.2882873],"study_design_scores_gemma":[0.0008893152,0.001384061,0.4940917,0.0006793568,0.003653388,0.02963904,0.001114398,0.3056456,0.03503494,0.091321,0.03632172,0.0002255971],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.6275827,0.003817944,0.3023425,0.001260185,0.0002566966,0.0005632297,0.05686001,0.004627305,0.002689522],"genre_scores_gemma":[0.7825532,0.0005553719,0.1556183,0.0003340971,0.0001298362,0.0004256901,0.05883495,0.0002469123,0.00130151],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.005648231,"threshold_uncertainty_score":0.01772881,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1591820342381299,"score_gpt":0.3764547576798917,"score_spread":0.2172727234417618,"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."}}