{"id":"W2332471229","doi":"10.1142/9789812774118_0030","title":"COMBINING VALIDITY INDEXES AND MULTI-OBJECTIVE OPTIMIZATION BASED CLUSTERING","year":2006,"lang":"en","type":"article","venue":"Applied Artificial Intelligence","topic":"Advanced Manufacturing and Logistics Optimization","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Cluster analysis; Artificial intelligence; 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":[],"consensus_categories":[],"category_scores_codex":[0.0001005068,0.0001538097,0.0001279429,0.00008020832,0.0001374159,0.00006745755,0.00006848165,0.00007848715,0.00001559828],"category_scores_gemma":[0.00002433761,0.0001725236,0.00001870179,0.0001228616,0.00007089733,0.00008009256,0.00002536217,0.0001310294,0.000008435251],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004489395,"about_ca_system_score_gemma":0.00000677754,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003671222,"about_ca_topic_score_gemma":0.00005726754,"domain_scores_codex":[0.9992415,0.000011064,0.0002507178,0.0002097868,0.0000904499,0.0001965036],"domain_scores_gemma":[0.9996641,0.00010356,0.00004449299,0.0001187396,0.00003126359,0.00003788928],"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":[0.00001490235,0.0000222624,0.00002533775,0.00001906566,0.000003422568,9.377129e-7,0.00008156044,0.9888716,0.0006614738,0.004195476,0.000004205189,0.006099793],"study_design_scores_gemma":[0.0000590432,0.00001144524,0.00005815917,0.00000993624,0.000008143497,6.326621e-7,0.00007651129,0.9241174,0.07064822,0.004814785,0.00001295512,0.0001827005],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003264284,0.0000236239,0.9939962,0.000008694887,0.0001674585,0.0001949269,0.000004686978,0.0003609957,0.001979142],"genre_scores_gemma":[0.8510346,0.00001219585,0.1487864,0.00001683602,0.0000617163,0.00002775694,0.00002748894,0.00002517392,0.000007767466],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8477704,"threshold_uncertainty_score":0.7035307,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03834915915643689,"score_gpt":0.2500013550177306,"score_spread":0.2116521958612937,"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."}}