{"id":"W53285091","doi":"10.5220/0002292601520159","title":"EXPLORATIVE DATA MINING FOR THE SIZING OF POPULATION GROUPS","year":2009,"lang":"en","type":"article","venue":"","topic":"Data Mining Algorithms and Applications","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Sizing; Computer science; Population; Data science; Data mining; Chemistry; Environmental health; Medicine","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":[0.007047169,0.0007419481,0.001552657,0.004957896,0.001454249,0.002318023,0.002565401,0.001164402,0.01608964],"category_scores_gemma":[0.05665407,0.000569015,0.00103292,0.004122097,0.0007459053,0.002953479,0.001888111,0.001203959,0.006238589],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006277565,"about_ca_system_score_gemma":0.001963086,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000975219,"about_ca_topic_score_gemma":0.001909686,"domain_scores_codex":[0.9957032,0.00113898,0.00036163,0.0008146035,0.001785101,0.0001965202],"domain_scores_gemma":[0.96538,0.01816812,0.003027112,0.00536557,0.007030385,0.001028833],"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":[0.0007740657,0.0002418512,0.07603086,0.001108797,0.0003205745,0.0005925552,0.0009948361,0.04172547,0.006782611,0.0295109,0.06978449,0.7721331],"study_design_scores_gemma":[0.0003784815,0.0006716686,0.0521541,0.0005983665,0.0003510145,0.001249049,0.002128619,0.6308236,0.03173606,0.1714796,0.1081606,0.0002688275],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2647779,0.001893772,0.6741806,0.007716753,0.002242308,0.001843777,0.01735283,0.005869348,0.02412272],"genre_scores_gemma":[0.7339459,0.0006637876,0.2396683,0.0002744801,0.0006754603,0.001054836,0.008624883,0.000446949,0.0146455],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01608964,"threshold_uncertainty_score":0.05382526,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1138423251789578,"score_gpt":0.3366299890415069,"score_spread":0.222787663862549,"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."}}