{"id":"W2370156110","doi":"","title":"Cluster Analysis and Visualization Enhanced Genetic Algorithm——II. Analysis of Cases and Validation","year":2004,"lang":"en","type":"article","venue":"","topic":"Advanced Clustering Algorithms Research","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"CAE (Canada)","funders":"","keywords":"Visualization; Computer science; Consistency (knowledge bases); Cluster (spacecraft); Robustness (evolution); Data mining; Dimension (graph theory); Algorithm; Process (computing); Cluster analysis; Genetic algorithm; Machine learning; Artificial intelligence; Mathematics; Chemistry","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":[0.0001883596,0.0001199282,0.000299933,0.001081528,0.0001250998,0.00009388705,0.0002028467,0.00005051295,0.00001440799],"category_scores_gemma":[0.0000801994,0.0001106351,0.00007383749,0.004027469,0.00007843831,0.0003955947,0.0003550898,0.00004601461,8.508347e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004590932,"about_ca_system_score_gemma":0.00002679234,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003413153,"about_ca_topic_score_gemma":0.0001212703,"domain_scores_codex":[0.9986742,0.000061709,0.0002868009,0.0004431983,0.0003426357,0.0001914869],"domain_scores_gemma":[0.9991019,0.0001438772,0.0001067891,0.0003665756,0.0001885297,0.00009234227],"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":[0.00002336901,0.0002890053,0.006033055,0.00008452724,0.005226277,0.00003789278,0.00436933,0.4647474,0.01088149,0.003769278,0.000007419346,0.504531],"study_design_scores_gemma":[0.0004154957,0.0001475772,0.0334017,0.00000652021,0.0007284498,0.000009540513,0.00004686139,0.9240197,0.04048241,0.0005669546,0.000007939525,0.0001668588],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2924785,0.00006117523,0.7072156,0.00007940058,0.00001323484,0.00008465496,0.000004281723,0.0000393105,0.00002387139],"genre_scores_gemma":[0.7049096,0.00008513296,0.2948375,0.0000392516,0.000008233522,0.000007851412,0.00001503885,0.000004902236,0.00009246789],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.5043641,"threshold_uncertainty_score":0.4511569,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01594593255158025,"score_gpt":0.3218239109678345,"score_spread":0.3058779784162542,"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."}}