{"id":"W1504062128","doi":"10.1007/978-3-540-73451-2_12","title":"The Art of Granular Computing","year":2007,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Rough Sets and Fuzzy Logic","field":"Computer Science","cited_by":136,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Regina","funders":"","keywords":"Granular computing; Computer science; CLARITY; Heuristics; Context (archaeology); Fuzzy set; Set (abstract data type); Range (aeronautics); Rough set; Theoretical computer science; Fuzzy logic; Artificial intelligence; Data science; Programming language","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":[0.002986936,0.0008237502,0.001551506,0.002261514,0.001637994,0.008536611,0.001616162,0.002492714,0.008098332],"category_scores_gemma":[0.008149347,0.0008918229,0.001243206,0.003325219,0.01235271,0.01225145,0.00323578,0.005774227,0.001653997],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002275499,"about_ca_system_score_gemma":0.001478979,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002148998,"about_ca_topic_score_gemma":0.001447272,"domain_scores_codex":[0.9979078,0.0006797437,0.0001537977,0.0003574401,0.0007605772,0.0001405998],"domain_scores_gemma":[0.997295,0.001509959,0.0001084471,0.0007221996,0.0002455406,0.0001189449],"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":[0.000007871526,0.000003983119,0.00003278717,0.00005211419,0.00000840705,0.00001225011,0.00008047031,0.0007368174,0.00007911832,0.9858359,0.003614588,0.009535722],"study_design_scores_gemma":[0.000003726894,0.000003020121,0.00003559011,0.00003881099,0.000004439065,0.0000187918,0.0000294003,0.001772035,0.00005834727,0.9731529,0.02487649,0.000006472559],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.007450234,0.09996276,0.5711013,0.03426287,0.005986953,0.0001179666,0.000615248,0.0007725795,0.2797301],"genre_scores_gemma":[0.4486374,0.05944343,0.3988035,0.007327509,0.00875311,0.0005714765,0.0006422288,0.000496257,0.07532512],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.008536611,"threshold_uncertainty_score":0.02709162,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02243376697341786,"score_gpt":0.2530389920688473,"score_spread":0.2306052250954294,"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."}}