{"id":"W1492208811","doi":"10.1007/3-540-44886-1_44","title":"A Genetic K-means Clustering Algorithm Applied to Gene Expression Data","year":2003,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Gene expression and cancer classification","field":"Biochemistry, Genetics and Molecular Biology","cited_by":29,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Cluster analysis; Computer science; Computational biology; Algorithm; Data mining; Biology; Artificial intelligence","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":[0.001384632,0.001179527,0.001921979,0.001675275,0.001947372,0.00133776,0.002680437,0.001483721,0.003065956],"category_scores_gemma":[0.002603955,0.0009306206,0.00207253,0.003280101,0.0007482251,0.0007720896,0.001222176,0.001522596,0.00267717],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001155086,"about_ca_system_score_gemma":0.002513973,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02238317,"about_ca_topic_score_gemma":0.0231449,"domain_scores_codex":[0.9989864,0.000196237,0.00006911855,0.0002920489,0.0003999037,0.00005631148],"domain_scores_gemma":[0.999188,0.0002550902,0.00003834253,0.0001064548,0.0003797761,0.00003233645],"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":[0.0001952556,0.0001397235,0.001026339,0.000292996,0.0003623546,0.0001719021,0.0003154238,0.1505929,0.02174727,0.005623512,0.01076834,0.8087639],"study_design_scores_gemma":[0.00006913958,0.00006908928,0.001776663,0.00004092816,0.0001247618,0.0002733149,0.00008392396,0.9614713,0.01193494,0.01249554,0.01157511,0.00008530559],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.003426901,0.0001566837,0.9920661,0.00007178368,0.0001005598,0.000111411,0.0001422421,0.003343811,0.000580401],"genre_scores_gemma":[0.01127229,0.0001050694,0.9865199,0.00004076798,0.00002319569,0.000168903,0.0003266523,0.0002684484,0.001274688],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02238317,"threshold_uncertainty_score":0.04450572,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02248543993476052,"score_gpt":0.2616032378541575,"score_spread":0.2391177979193969,"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."}}