{"id":"W1975251650","doi":"10.1016/j.ijar.2007.06.014","title":"Probabilistic approach to rough sets","year":2007,"lang":"en","type":"article","venue":"International Journal of Approximate Reasoning","topic":"Rough Sets and Fuzzy Logic","field":"Computer Science","cited_by":237,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Regina","funders":"","keywords":"Rough set; Probabilistic logic; Reduct; Dependency (UML); Property (philosophy); Probabilistic relevance model; Computer science; Measure (data warehouse); Monotonic function; Set (abstract data type); Data mining; Mathematics; Computation; Artificial intelligence; Probabilistic analysis of algorithms; Algorithm","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":[0.005837019,0.0010574,0.002589064,0.005028299,0.001321958,0.004948305,0.002823197,0.001850101,0.004588502],"category_scores_gemma":[0.02310684,0.001483826,0.002731916,0.004099086,0.003364177,0.006588361,0.00248106,0.003622536,0.0007836464],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002208901,"about_ca_system_score_gemma":0.001460219,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001634372,"about_ca_topic_score_gemma":0.001660617,"domain_scores_codex":[0.9924006,0.0026306,0.0004733525,0.0006473479,0.003597055,0.0002510226],"domain_scores_gemma":[0.9870933,0.009050102,0.0007565996,0.001379818,0.001470365,0.0002497963],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00001379545,0.00001566558,0.0001830079,0.0001002575,0.0000719114,0.00005225039,0.00008506738,0.02463315,0.0001579516,0.9594277,0.0008085622,0.0144507],"study_design_scores_gemma":[0.000007498045,0.00001249072,0.0001307422,0.00001972294,0.00002758349,0.00006483799,0.00001958238,0.0654109,0.00009482499,0.9312893,0.002906124,0.00001636443],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002379872,0.001748442,0.989624,0.001075419,0.0001606977,0.00002773128,0.00009576005,0.00007870174,0.004809313],"genre_scores_gemma":[0.3938978,0.007256501,0.5840566,0.0007358264,0.001941679,0.0004511492,0.0004867664,0.0001141431,0.01105948],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005837019,"threshold_uncertainty_score":0.03086948,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01987984125818776,"score_gpt":0.2843185250988401,"score_spread":0.2644386838406523,"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."}}