{"id":"W2499411820","doi":"10.4018/978-1-60566-902-1.ch017","title":"Unifying Rough Set Analysis and Formal Concept Analysis Based on a Logic Approach to Granular Computing","year":2010,"lang":"en","type":"book-chapter","venue":"IGI Global eBooks","topic":"Rough Sets and Fuzzy Logic","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Regina","funders":"","keywords":"Granular computing; Intension; Rough set; Formal concept analysis; Abstraction; Computer science; Granularity; Theoretical computer science; Mathematics; Heuristics; Artificial intelligence; Algorithm; 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":[0.002568215,0.001083164,0.001194428,0.003393919,0.0007291342,0.005927857,0.001564101,0.001328692,0.004235386],"category_scores_gemma":[0.003290509,0.0006153161,0.002143116,0.003449435,0.003418606,0.006290466,0.001648389,0.002972833,0.001606238],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002531959,"about_ca_system_score_gemma":0.001403546,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001160521,"about_ca_topic_score_gemma":0.001233632,"domain_scores_codex":[0.9983708,0.000479505,0.0001320416,0.0002193754,0.000718343,0.00007993389],"domain_scores_gemma":[0.9986507,0.0009387768,0.00008178249,0.0001304968,0.0001650191,0.00003320602],"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":[0.000009578265,0.00001310888,0.00005811144,0.0002536122,0.00003026142,0.00008538237,0.0003169417,0.005722363,0.0005090138,0.9308048,0.003326908,0.05887008],"study_design_scores_gemma":[0.000008373276,0.0000224965,0.0001403297,0.0002252515,0.000026576,0.0001550862,0.0001157184,0.02077631,0.0006393398,0.9116413,0.06622242,0.00002682716],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001649657,0.01336967,0.9351961,0.002265163,0.0005513913,0.0001058659,0.0001127459,0.0002558533,0.04649365],"genre_scores_gemma":[0.08398068,0.02592137,0.859063,0.001157799,0.001058309,0.0003470826,0.00039761,0.0001972789,0.02787694],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005927857,"threshold_uncertainty_score":0.01837075,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02585534874477662,"score_gpt":0.2518394311738974,"score_spread":0.2259840824291208,"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."}}