{"id":"W2142280242","doi":"10.1007/978-3-7908-1791-1_5","title":"Granular Computing Using Information Tables","year":2002,"lang":"en","type":"book-chapter","venue":"Studies in fuzziness and soft computing","topic":"Rough Sets and Fuzzy Logic","field":"Computer Science","cited_by":100,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Regina","funders":"","keywords":"Granular computing; Rough set; Computer science; Universe; Simple (philosophy); Theoretical computer science; Object (grammar); Set (abstract data type); Granule (geology); Data mining; Artificial intelligence; Programming language; Physics","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":[0.001264778,0.0007843266,0.001112188,0.001938925,0.0006919812,0.006302008,0.001168763,0.001152652,0.005939718],"category_scores_gemma":[0.003465992,0.0004952368,0.001246314,0.003052071,0.002111616,0.008132909,0.001645641,0.00198329,0.00132032],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001729395,"about_ca_system_score_gemma":0.0008611513,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00150147,"about_ca_topic_score_gemma":0.0008623605,"domain_scores_codex":[0.9990842,0.0002289235,0.0000857563,0.0001538345,0.0003725874,0.00007470587],"domain_scores_gemma":[0.9991346,0.0004944458,0.0000532316,0.0001820301,0.00008835082,0.00004728041],"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":[0.00002415667,0.00001033786,0.00008598802,0.000114915,0.00002244497,0.00007160907,0.00009702003,0.01481327,0.0005008556,0.9509661,0.004071069,0.02922222],"study_design_scores_gemma":[0.00001142632,0.00001563221,0.000105659,0.00007683934,0.00002211726,0.00009061116,0.00003801382,0.05897553,0.0005756225,0.9086785,0.03138665,0.00002350872],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.007821274,0.01147204,0.8868182,0.002980545,0.0008328839,0.0001714454,0.0004782717,0.0009186002,0.08850671],"genre_scores_gemma":[0.3801774,0.01790116,0.5645586,0.0009854619,0.001210124,0.0003893199,0.0008666649,0.0002359789,0.03367525],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006302008,"threshold_uncertainty_score":0.01987034,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06698553509141224,"score_gpt":0.2822353340469533,"score_spread":0.215249798955541,"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."}}