{"id":"W4244238354","doi":"10.1109/grc.2007.4403141","title":"Comparison of Machine Learning and Pattern Discovery Algorithms for the Prediction of Human Single Nucleotide Polymorphisms","year":2007,"lang":"en","type":"article","venue":"2007 IEEE International Conference on Granular Computing (GRC 2007)","topic":"Machine Learning in Bioinformatics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Machine learning; Single-nucleotide polymorphism; Artificial intelligence; Computational biology; Algorithm; Biology; Genetics; Genotype; Gene","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":[0.01520166,0.0009222346,0.001522372,0.004354323,0.0007311229,0.001765928,0.001836299,0.001686851,0.0006499456],"category_scores_gemma":[0.04208764,0.0005260101,0.001575932,0.004152918,0.0007291269,0.002637416,0.001079481,0.001423464,0.0003859549],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001283605,"about_ca_system_score_gemma":0.001782684,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003147065,"about_ca_topic_score_gemma":0.002496696,"domain_scores_codex":[0.9885788,0.004883884,0.00131391,0.001163167,0.003754108,0.0003060796],"domain_scores_gemma":[0.9504386,0.0422014,0.001213337,0.002650466,0.003193154,0.0003030019],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001106167,0.0003407035,0.01930386,0.0005757569,0.0009526253,0.0001311117,0.0001824828,0.3579806,0.002489924,0.01182974,0.001883218,0.6032239],"study_design_scores_gemma":[0.0001354122,0.000241696,0.004970083,0.00006067126,0.0001010601,0.0001816849,0.00007314898,0.975538,0.002569955,0.01458221,0.001504416,0.00004177481],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1596073,0.006110877,0.8257836,0.001200251,0.0001904546,0.0002422993,0.0003829528,0.003026139,0.003456196],"genre_scores_gemma":[0.3469779,0.002263216,0.6484844,0.0002844348,0.00007824296,0.0002914451,0.0008543702,0.0002021646,0.0005637991],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01520166,"threshold_uncertainty_score":0.08039498,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03891084354732889,"score_gpt":0.3301831386151906,"score_spread":0.2912722950678617,"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."}}