{"id":"W2113755034","doi":"10.1145/1569901.1570232","title":"Evolutionary clustering with arbitrary subspaces","year":2009,"lang":"en","type":"article","venue":"","topic":"Advanced Clustering Algorithms Research","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Cluster analysis; Linear subspace; Subspace topology; Computer science; Correlation clustering; Canopy clustering algorithm; Set (abstract data type); Constrained clustering; CURE data clustering algorithm; Evolutionary algorithm; Algorithm; Data mining; Mathematics; Mathematical optimization; Theoretical computer science; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":true,"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":[0.00008988009,0.0001132898,0.00009959329,0.0001043631,0.0001235981,0.0001003755,0.0006747966,0.00003069457,0.00001752795],"category_scores_gemma":[0.000009715063,0.0000870455,0.00002337668,0.000418468,0.00003870723,0.0008405353,0.0001777988,0.0001521748,0.00005071105],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005491793,"about_ca_system_score_gemma":0.00006053905,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001092812,"about_ca_topic_score_gemma":0.00000739329,"domain_scores_codex":[0.9988065,0.00002472506,0.0001028743,0.0003394102,0.0003690997,0.0003573482],"domain_scores_gemma":[0.9992869,0.00004253211,0.00002528057,0.0004688306,0.00006079163,0.000115696],"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":[0.000177576,0.0005041892,0.001596701,0.00006392654,0.00007539919,0.001101822,0.00151514,0.03661639,0.006508644,0.1221597,0.004068399,0.8256121],"study_design_scores_gemma":[0.0006452008,0.0007393569,0.02491096,0.00004946184,0.000002056593,0.0003993792,0.00006684585,0.956364,0.002315786,0.01095854,0.003090268,0.0004581804],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.003983485,0.00011953,0.9719514,0.002875761,0.00005167632,0.0001038782,3.159449e-7,0.0004403307,0.02047367],"genre_scores_gemma":[0.3554325,0.00001184461,0.642129,0.0004548086,0.00005293044,0.000006087525,7.509934e-7,0.000006295742,0.001905813],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9197476,"threshold_uncertainty_score":0.3549612,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01267447780576022,"score_gpt":0.2639241954487666,"score_spread":0.2512497176430064,"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."}}