{"id":"W1538131118","doi":"10.1007/11548706_38","title":"Relevant Attribute Discovery in High Dimensional Data Based on Rough Sets and Unsupervised Classification: Application to Leukemia Gene Expressions","year":2005,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Rough Sets and Fuzzy Logic","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"National Research Council Canada","funders":"","keywords":"Rough set; Artificial intelligence; Computer science; Pattern recognition (psychology); High dimensional; Data mining","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0008086455,0.000503148,0.0004842334,0.0006440309,0.0002896378,0.0005289991,0.003634847,0.000303476,0.000005961055],"category_scores_gemma":[0.00007680642,0.0004191893,0.00004920424,0.0007265698,0.0003594999,0.0009745259,0.002204365,0.0006582577,0.00002933284],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005404314,"about_ca_system_score_gemma":0.0006772656,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005510718,"about_ca_topic_score_gemma":0.00009239606,"domain_scores_codex":[0.9952384,0.00006123953,0.000590113,0.002522169,0.001027158,0.0005609025],"domain_scores_gemma":[0.995756,0.0005256413,0.0002152729,0.00316549,0.000110977,0.0002266074],"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":[0.00003138315,0.00009007262,0.0001571223,0.00002399953,0.000005482277,0.00005413768,0.0001906417,0.403563,0.0007083284,0.008472337,0.0001686682,0.5865349],"study_design_scores_gemma":[0.0004347487,0.0001216793,0.0049698,0.0003125506,0.000005296946,0.00001580783,1.109522e-7,0.9806306,0.0001879189,0.01148847,0.001303302,0.0005297303],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.000999889,0.0001911701,0.9916851,0.005521168,0.0004950479,0.0006924162,0.0001065943,0.00008580137,0.0002228051],"genre_scores_gemma":[0.4567471,0.00005204128,0.5382055,0.004344654,0.0003118387,0.00003693075,0.0002278923,0.00002819907,0.00004585753],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.5860052,"threshold_uncertainty_score":0.999826,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03730734188509197,"score_gpt":0.2665162858400922,"score_spread":0.2292089439550003,"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."}}