{"id":"W1529665683","doi":"","title":"Sensor, Filter, and Fusion Models with Rough Petri Nets","year":2001,"lang":"en","type":"article","venue":"Fundamenta Informaticae","topic":"Petri Nets in System Modeling","field":"Computer Science","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"Petri net; Context (archaeology); Rough set; Relevance (law); Sensor fusion; Filter (signal processing); Process architecture; Stochastic Petri net; Computer science; Fusion rules; Wireless sensor network; Theoretical computer science; Artificial intelligence; Algorithm; Data mining; Computer vision","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":[0.002064602,0.001057005,0.001012629,0.001031018,0.0008092773,0.00265433,0.001807528,0.001372411,0.001857407],"category_scores_gemma":[0.002938993,0.0006132507,0.002271318,0.000946768,0.002309544,0.003983301,0.001380063,0.001708032,0.0004426991],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001864882,"about_ca_system_score_gemma":0.001429746,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007658405,"about_ca_topic_score_gemma":0.004970839,"domain_scores_codex":[0.9985746,0.0004384374,0.0001037235,0.0002903678,0.0004316181,0.0001612588],"domain_scores_gemma":[0.9985104,0.0008194396,0.0002182401,0.0001780731,0.000175753,0.0000980758],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00009511892,0.00003558869,0.0004111934,0.00007254466,0.00004964168,0.000191028,0.0002160759,0.5949934,0.001752941,0.3931925,0.0003399706,0.008650078],"study_design_scores_gemma":[0.0000198809,0.00003871146,0.0001024526,0.00001547274,0.00002901543,0.00004059136,0.00003074452,0.8504816,0.0009527575,0.1460586,0.002209081,0.00002110339],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.008435871,0.0002640717,0.9879158,0.0001592287,0.00003986085,0.00003602185,0.0000786308,0.0001897159,0.002880841],"genre_scores_gemma":[0.579042,0.001128469,0.4111581,0.0001596546,0.0001144008,0.0003409975,0.0003504003,0.00008556599,0.00762042],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007658405,"threshold_uncertainty_score":0.01522762,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03795754249442898,"score_gpt":0.2407896860156395,"score_spread":0.2028321435212106,"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."}}