{"id":"W2031366103","doi":"10.1007/s10115-002-8192-7","title":"Knowledge Discovery Through Self-Organizing Maps: Data Visualization and Query Processing","year":2002,"lang":"en","type":"article","venue":"Knowledge and Information Systems","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":29,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Knowledge extraction; Visualization; Data mining; Set (abstract data type); Information retrieval; Heuristic; Premise; Data visualization; Information visualization; Data science; 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":[0.003234598,0.0008284166,0.0009413622,0.00608657,0.001046246,0.006537509,0.001265429,0.001090137,0.003126432],"category_scores_gemma":[0.01111563,0.0005867595,0.0008446951,0.007684327,0.001112437,0.005718411,0.002404532,0.001013162,0.0008773102],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009627545,"about_ca_system_score_gemma":0.001888764,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00485451,"about_ca_topic_score_gemma":0.004842831,"domain_scores_codex":[0.9979317,0.0007632367,0.0001245036,0.0002532849,0.0008172108,0.0001100823],"domain_scores_gemma":[0.9951494,0.002845012,0.000278793,0.0007516456,0.0007719217,0.0002032165],"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":[0.0005752888,0.0003844813,0.007883566,0.001133147,0.0003294168,0.0003587412,0.003068978,0.04686737,0.01023592,0.1034315,0.02637996,0.7993516],"study_design_scores_gemma":[0.00008294633,0.0000982123,0.003520109,0.0001356909,0.0001903307,0.0004154201,0.00184674,0.6693265,0.03077017,0.2531922,0.04029699,0.000124786],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03805707,0.002284454,0.9440732,0.001755565,0.0001329127,0.0001755873,0.001265947,0.006840509,0.0054146],"genre_scores_gemma":[0.365652,0.002379931,0.627491,0.0001520131,0.0001161811,0.0002477629,0.001324672,0.0005537653,0.002082688],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.006537509,"threshold_uncertainty_score":0.01710635,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04714598115889816,"score_gpt":0.3028134019006688,"score_spread":0.2556674207417706,"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."}}