{"id":"W2294778980","doi":"10.1109/tsmca.2005.843381","title":"Granular Mappings","year":2005,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics - Part A Systems and Humans","topic":"Rough Sets and Fuzzy Logic","field":"Computer Science","cited_by":70,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Granulation; Granular computing; Cluster analysis; Representation (politics); Set (abstract data type); Fuzzy set; Fuzzy logic; Computer science; Granular material; Mathematics; Data mining; Expression (computer science); Algorithm; Rough set; Artificial intelligence; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003425099,0.0003023897,0.0004097776,0.0001782994,0.0004980433,0.0007559427,0.0003128926,0.0001524661,0.000009233702],"category_scores_gemma":[8.388087e-7,0.000259241,0.0000857192,0.0001585319,0.0001057163,0.0002760769,0.000006648295,0.0002230306,0.00007360843],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003839423,"about_ca_system_score_gemma":0.0000197831,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003184809,"about_ca_topic_score_gemma":0.00009083545,"domain_scores_codex":[0.9980485,0.0001100223,0.0005118983,0.0005893791,0.0003404054,0.0003997787],"domain_scores_gemma":[0.9989735,0.00005030869,0.0001306869,0.0005443891,0.00006249839,0.0002386129],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001188567,0.002118549,0.001035744,0.002907908,0.0008289831,0.0002630826,0.03955022,0.052372,0.001512121,0.7193125,0.03339895,0.1465811],"study_design_scores_gemma":[0.001818246,0.0006673549,0.00073037,0.0006023372,0.0001055314,0.0004304003,0.001075454,0.1776666,0.0001217177,0.0003465288,0.8152235,0.001212043],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05871952,0.006435751,0.9144805,0.0007560898,0.003341829,0.001257908,0.00005134696,0.0004833207,0.01447375],"genre_scores_gemma":[0.9937142,0.0005295732,0.0004543874,0.0001540525,0.0002933969,0.00009984407,0.00000156547,0.00002235143,0.004730632],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9349947,"threshold_uncertainty_score":0.999986,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02246933669898328,"score_gpt":0.2235627118005636,"score_spread":0.2010933751015803,"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."}}