{"id":"W7030358319","doi":"","title":"Multi-objective Evolutionary Optimization for Visual Data Mining with Virtual Reality Spaces: Application to Alzheimer Gene Expressions","year":2006,"lang":"en","type":"article","venue":"NPARC","topic":"Composite Structure Analysis and Optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Research Council Canada","keywords":"Context (archaeology); Set (abstract data type); Representation (politics); Virtual reality; Class (philosophy); Similarity (geometry); Range (aeronautics); Optimization problem; Pattern recognition (psychology)","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007495295,0.0001367561,0.000142233,0.00009769671,0.0001398472,0.00003904185,0.0001545548,0.00006061286,0.0000312517],"category_scores_gemma":[0.0000115459,0.0001252444,0.00002694548,0.000284562,0.00001639203,0.0002164304,0.00005441878,0.00004782955,0.000001926464],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005732253,"about_ca_system_score_gemma":0.00001866389,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004423237,"about_ca_topic_score_gemma":0.0001012835,"domain_scores_codex":[0.9991727,0.0000191963,0.0001894988,0.0003185943,0.0001424619,0.0001574966],"domain_scores_gemma":[0.9993753,0.00004469178,0.00004898527,0.0003607694,0.0001168591,0.000053395],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003270269,0.00002915757,0.0001534293,0.000004663646,0.0000605682,2.115309e-7,0.00009702556,0.969185,0.02649056,0.00005809759,0.001896221,0.001992396],"study_design_scores_gemma":[0.0003085474,0.00004757345,0.001549419,0.00001267268,0.0001243237,0.000001584022,0.00007056478,0.9944328,0.002782011,0.00002351121,0.0004774834,0.0001695109],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01052005,0.00005248273,0.988163,0.00007020197,0.00004591063,0.0004308098,0.0001125873,0.0001416099,0.0004633537],"genre_scores_gemma":[0.5949756,0.000004547984,0.4029358,0.00001504016,0.0001308035,0.00007239915,0.001824875,0.00002250643,0.00001838098],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.5852271,"threshold_uncertainty_score":0.5107317,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01841254683143743,"score_gpt":0.2710310730762015,"score_spread":0.2526185262447641,"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."}}