{"id":"W2952848794","doi":"10.1101/649368","title":"Exautomate: A user-friendly tool for region-based rare variant association analysis (RVAA)","year":2019,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Genetic Associations and Epidemiology","field":"Biochemistry, Genetics and Molecular Biology","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"R package; Context (archaeology); Genetic architecture; Computer science; Association (psychology); Association test; Kernel (algebra); Data science; Data mining; Machine learning; Computational biology; Phenotype; Biology; Genetics; Psychology; Genotype; Gene; Mathematics; Single-nucleotide polymorphism","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":[0.007341558,0.003047299,0.002650864,0.003361471,0.0008111274,0.00301999,0.004111276,0.001620962,0.08940342],"category_scores_gemma":[0.01868197,0.002366573,0.003365317,0.001806021,0.001017882,0.002406313,0.004322851,0.003097552,0.04214574],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005966728,"about_ca_system_score_gemma":0.002026669,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00160371,"about_ca_topic_score_gemma":0.002184164,"domain_scores_codex":[0.9977889,0.0006392123,0.0002835045,0.0005000685,0.0006255795,0.0001628094],"domain_scores_gemma":[0.9889558,0.008319498,0.0006141784,0.00116954,0.0005926427,0.0003482379],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002882403,0.0004568875,0.01331109,0.003282273,0.002187227,0.002273356,0.000875461,0.01014627,0.01542113,0.0161652,0.7289915,0.2040072],"study_design_scores_gemma":[0.00368493,0.0004678081,0.02374717,0.001123865,0.0008500877,0.004214197,0.000306497,0.2113337,0.06475042,0.0879218,0.6006441,0.0009554075],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"software","genre_gemma":"methods","genre_scores_codex":[0.003474853,0.0003753717,0.4400599,0.0003468517,0.0003036145,0.000298712,0.03318686,0.5200319,0.001922039],"genre_scores_gemma":[0.04724259,0.0006797684,0.6753299,0.001236367,0.0003308111,0.003170979,0.06148571,0.1996052,0.01091869],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.08940342,"threshold_uncertainty_score":0.2990842,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01001365109254212,"score_gpt":0.2304876534830782,"score_spread":0.2204740023905361,"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."}}