{"id":"W1962722916","doi":"10.1109/nafips.1997.624041","title":"Information granularity uncertainty principle: contingency tables and Petri net representations","year":2002,"lang":"en","type":"article","venue":"","topic":"Rough Sets and Fuzzy Logic","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"Petri net; Granularity; Dynamical systems theory; Computer science; Theoretical computer science; Constructive; Component (thermodynamics); Process architecture; Set (abstract data type); Simple (philosophy); Dynamical system (definition); Data mining; Algorithm; Process (computing); 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":[0.004508258,0.000589497,0.0008877892,0.003312734,0.0009815061,0.003814304,0.00148103,0.0009014226,0.00305858],"category_scores_gemma":[0.01504276,0.0004922431,0.001129152,0.002839956,0.003141871,0.006665132,0.001548446,0.001852474,0.0002936619],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001517824,"about_ca_system_score_gemma":0.001106504,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001503843,"about_ca_topic_score_gemma":0.001155383,"domain_scores_codex":[0.9976345,0.0008314726,0.0001822456,0.0003384223,0.0008606849,0.000152699],"domain_scores_gemma":[0.9912072,0.006245327,0.0008492708,0.0009758379,0.0005209531,0.0002015103],"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":[0.00003243716,0.00001209768,0.0003607578,0.00005619277,0.00002344224,0.00009669451,0.0001530131,0.03856168,0.0003000487,0.9386212,0.0006506561,0.02113173],"study_design_scores_gemma":[0.000006481668,0.00001141772,0.0001422007,0.00002717856,0.00001113244,0.0000482154,0.00004139914,0.08079024,0.000268457,0.9167005,0.001936911,0.00001599283],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.009301686,0.0005230524,0.9836109,0.0006446298,0.00006553747,0.00005744764,0.0002651396,0.0001400969,0.005391647],"genre_scores_gemma":[0.5131096,0.001028845,0.4828345,0.0002544518,0.0002955164,0.0002732048,0.0004613967,0.00007296798,0.001669564],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004508258,"threshold_uncertainty_score":0.02384222,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02216524546849701,"score_gpt":0.2501504149080667,"score_spread":0.2279851694395697,"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."}}