{"id":"W2166107822","doi":"10.4018/jcini.2007100107","title":"Interactive Classification Using a Granule Network","year":2007,"lang":"en","type":"article","venue":"International Journal of Cognitive Informatics and Natural Intelligence","topic":"Rough Sets and Fuzzy Logic","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Regina","funders":"","keywords":"Computer science; Machine learning; Artificial intelligence; Granular computing; Automation; Decision tree; Process (computing); Data mining; Rough set","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":[0.001532001,0.0005084848,0.0008610045,0.001966931,0.0009276417,0.002736967,0.001228548,0.001149272,0.003249464],"category_scores_gemma":[0.00583597,0.0002696994,0.0008357299,0.001949866,0.001624634,0.004508098,0.002122042,0.0008151248,0.0004601429],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001399273,"about_ca_system_score_gemma":0.0006597803,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003819317,"about_ca_topic_score_gemma":0.002220328,"domain_scores_codex":[0.9988186,0.0003512704,0.00009241154,0.0002876178,0.0003138765,0.0001362689],"domain_scores_gemma":[0.9976647,0.001279867,0.0002824704,0.0003565184,0.0002974006,0.0001190357],"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":[0.0006550188,0.000156864,0.01116903,0.0002055186,0.0001432698,0.0005806257,0.001219118,0.2970629,0.009864411,0.337371,0.003971547,0.3376007],"study_design_scores_gemma":[0.00001566111,0.00004825053,0.0009747437,0.00002534294,0.00003719367,0.00007788707,0.0001015433,0.9270365,0.001740817,0.06716228,0.002763322,0.00001642376],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.06623451,0.0002392381,0.9271535,0.0003493017,0.00004562214,0.0001105794,0.0001202683,0.0006354303,0.005111514],"genre_scores_gemma":[0.7677959,0.0002954739,0.2278819,0.00008966688,0.00005928394,0.0002295827,0.0003274503,0.00009065698,0.00323002],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003819317,"threshold_uncertainty_score":0.01087058,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03429355271945284,"score_gpt":0.3313910547259428,"score_spread":0.2970975020064899,"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."}}