{"id":"W1977122250","doi":"10.5539/cis.v3n1p152","title":"A Knowledge Innovation Algorithm Based on Granularity","year":2010,"lang":"en","type":"article","venue":"Computer and Information Science","topic":"Rough Sets and Fuzzy Logic","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Natural Science Foundation of China","keywords":"Granularity; Computer science; Knowledge base; Consistency (knowledge bases); sort; Granular computing; Knowledge space; Partition (number theory); Rough set; Algorithm; Data mining; Theoretical computer science; Measure (data warehouse); Artificial intelligence; Mathematics; Knowledge management; Information retrieval","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008936458,0.00009223392,0.00007778293,0.0005260064,0.0003689158,0.0007715478,0.0006797512,0.00004169356,0.000004311095],"category_scores_gemma":[0.00003755286,0.00007293261,0.00001602349,0.001932675,0.0002004853,0.006064921,0.0002067138,0.000173359,0.00006614892],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001406609,"about_ca_system_score_gemma":0.000145695,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003153283,"about_ca_topic_score_gemma":3.943861e-7,"domain_scores_codex":[0.9990472,0.00001180977,0.000231062,0.0001942347,0.0003219255,0.0001938128],"domain_scores_gemma":[0.9990721,0.00003976582,0.00008328717,0.0003726842,0.0003536947,0.00007846556],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[7.254565e-7,0.00002001606,0.0000817913,0.000004082962,3.141998e-7,2.176666e-7,0.0003219035,0.00005572135,0.00004213102,0.159782,0.0002640473,0.8394271],"study_design_scores_gemma":[0.0002159771,0.00007802449,0.01564525,0.000005151457,4.161902e-7,0.000007078817,0.000002554705,0.9631177,0.0002244454,0.001492081,0.01910716,0.0001041306],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.007313878,0.000002034144,0.9764292,0.0004321491,0.001020139,0.000107347,0.000001708081,0.000106315,0.01458722],"genre_scores_gemma":[0.5566998,0.000001821701,0.4401878,0.003022662,0.00007304045,0.000005531771,0.000004988017,0.00000128561,0.000003105454],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.963062,"threshold_uncertainty_score":0.7440053,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01416924665070338,"score_gpt":0.25616078415722,"score_spread":0.2419915375065167,"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."}}