{"id":"W2025295306","doi":"10.1016/j.camwa.2008.10.043","title":"Criteria for choosing a rough set model","year":2008,"lang":"en","type":"article","venue":"Computers & Mathematics with Applications","topic":"Rough Sets and Fuzzy Logic","field":"Computer Science","cited_by":74,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Regina","funders":"Faculty of Graduate Studies and Research, University of Alberta; Natural Sciences and Engineering Research Council of Canada; University of Regina","keywords":"Rough set; Dominance-based rough set approach; Probabilistic logic; Set (abstract data type); Data mining; Mathematics; Computer science; Decision model; Statistical model; Machine learning; 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":[0.0001200079,0.0001854722,0.0002308307,0.0000743983,0.0004305327,0.0001434299,0.0008945416,0.00005011396,0.000001503065],"category_scores_gemma":[0.000006117556,0.000150973,0.00007069601,0.0003258245,0.00007737689,0.0002569471,0.0001527353,0.00007912663,0.00002498008],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003461599,"about_ca_system_score_gemma":0.00008471696,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001632276,"about_ca_topic_score_gemma":6.045473e-7,"domain_scores_codex":[0.9988345,0.000009979005,0.0002784017,0.0003939896,0.0001874009,0.0002957409],"domain_scores_gemma":[0.9986016,0.0001430085,0.0001412297,0.0008768394,0.0001241823,0.0001131528],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000009967514,0.0006785119,0.00003270539,0.0002895303,0.00008607243,0.000008367848,0.01001293,0.02812839,0.0002139783,0.9150236,0.02404697,0.02146897],"study_design_scores_gemma":[0.0003077568,0.00004696371,0.00002290695,0.00002536625,0.00001133559,0.00009567859,0.0000168516,0.9267107,0.00004978197,0.0687755,0.003732528,0.000204632],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0008692734,0.00004165436,0.9951267,0.0007356662,0.0000442126,0.0009340863,0.00001403994,0.0002870222,0.001947303],"genre_scores_gemma":[0.07659849,0.0000143152,0.9221077,0.0004261055,0.00007537995,0.000665902,0.00001639246,0.00002036532,0.00007537026],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.8985823,"threshold_uncertainty_score":0.6156501,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06961082574663738,"score_gpt":0.2971579563900591,"score_spread":0.2275471306434217,"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."}}