{"id":"W2157911533","doi":"10.1109/cbms.2006.100","title":"Incorporating Gene Ontology in Clustering Gene Expression Data","year":2006,"lang":"en","type":"article","venue":"","topic":"Gene expression and cancer classification","field":"Biochemistry, Genetics and Molecular Biology","cited_by":45,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Cluster analysis; Data mining; Biological data; Computer science; Ontology; Gene ontology; Data integration; Expression (computer science); Measure (data warehouse); Artificial intelligence; Bioinformatics; Gene; Gene expression; Biology","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":[0.005915596,0.0007851337,0.001041598,0.003820961,0.001016732,0.002100637,0.001269802,0.0008159777,0.0003623216],"category_scores_gemma":[0.01047908,0.000373971,0.001216345,0.004941871,0.00114824,0.002439308,0.002245004,0.00108667,0.0003246624],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009762588,"about_ca_system_score_gemma":0.001751993,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003722069,"about_ca_topic_score_gemma":0.00450902,"domain_scores_codex":[0.9961099,0.001075734,0.0003792052,0.0008071406,0.001448801,0.0001792796],"domain_scores_gemma":[0.9972995,0.001128135,0.0002929094,0.0007075497,0.0004912106,0.00008065876],"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":[0.0004361888,0.0004554057,0.02340373,0.001204639,0.0006828109,0.0006194505,0.001225912,0.1521571,0.125539,0.07798839,0.001366949,0.6149204],"study_design_scores_gemma":[0.00009401063,0.0004916231,0.01885946,0.0002313743,0.000403099,0.001044939,0.0007503452,0.6381476,0.09181939,0.2100056,0.03790704,0.0002455694],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01978503,0.0002737217,0.9786412,0.00009984637,0.00002706497,0.0001195952,0.0002714036,0.0003307821,0.0004513222],"genre_scores_gemma":[0.1296044,0.0004108569,0.8676504,0.00008704017,0.0000283419,0.0002212259,0.001472917,0.00009742052,0.000427506],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005915596,"threshold_uncertainty_score":0.03128505,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02984900334608226,"score_gpt":0.2817890745918252,"score_spread":0.2519400712457429,"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."}}