{"id":"W1978034558","doi":"10.4061/2009/869093","title":"Data Integration in Genetics and Genomics: Methods and Challenges","year":2009,"lang":"en","type":"article","venue":"Human Genomics and Proteomics","topic":"Gene expression and cancer classification","field":"Biochemistry, Genetics and Molecular Biology","cited_by":150,"is_retracted":false,"has_abstract":true,"ca_institutions":"Public Health Ontario; University of Toronto; Hospital for Sick Children","funders":"Natural Sciences and Engineering Research Council of Canada; Genome Canada; Canadian Institutes of Health Research; Mitacs; Ontario Genomics; Ontario Genomics Institute","keywords":"Genomics; Computational biology; Data integration; Proteomics; Genome; Biology; Data type; Functional genomics; Data science; Computer science; Gene; Data mining; Genetics","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":[0.1235611,0.002439163,0.006415208,0.01288357,0.002972999,0.02339574,0.01250149,0.006394234,0.002408402],"category_scores_gemma":[0.1551989,0.002771225,0.004284524,0.02056749,0.01177804,0.02938051,0.01357746,0.01076006,0.002361108],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005138987,"about_ca_system_score_gemma":0.01064641,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005658049,"about_ca_topic_score_gemma":0.00226364,"domain_scores_codex":[0.8961759,0.06636189,0.008535424,0.007696742,0.02015678,0.001073264],"domain_scores_gemma":[0.7562124,0.198934,0.005963215,0.01963724,0.01656802,0.002685081],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001567979,0.0002199136,0.007803005,0.004400169,0.0007387197,0.0006764137,0.002120276,0.008494389,0.001219297,0.3367195,0.01944725,0.6180043],"study_design_scores_gemma":[0.00007071008,0.00008652862,0.002202278,0.002101048,0.0001465358,0.001367395,0.002073997,0.04272626,0.001177544,0.8488076,0.09900635,0.0002337414],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002470191,0.03558547,0.9211436,0.03501568,0.0009589467,0.0004423057,0.0006262054,0.00111608,0.002641422],"genre_scores_gemma":[0.03246553,0.02392478,0.9332039,0.004431481,0.002254366,0.001202743,0.001118485,0.000441142,0.0009575518],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.1235611,"threshold_uncertainty_score":0.6534612,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09538990105904042,"score_gpt":0.3624385403715629,"score_spread":0.2670486393125225,"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."}}