{"id":"W2088974536","doi":"10.1007/s005000100153","title":"An fMUX architecture: data modularization and mixed-mode system modeling","year":2002,"lang":"en","type":"article","venue":"Soft Computing","topic":"Neural Networks and Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Canadian Space Agency; University of Alberta","funders":"","keywords":"Multiplexer; Modular programming; Computer science; Modular design; Theoretical computer science; Fuzzy logic; Process (computing); Scheme (mathematics); Mode (computer interface); Granularity; Variable (mathematics); Architecture; Artificial intelligence; Distributed computing; Computer architecture; Topology (electrical circuits); Multiplexing; Mathematics; Programming language; Human–computer interaction","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":[],"consensus_categories":[],"category_scores_codex":[0.0001741673,0.0001108459,0.0001127677,0.00004463048,0.0003427512,0.0002655435,0.000932332,0.00003925352,5.874302e-7],"category_scores_gemma":[0.000009550644,0.0001063732,0.00001500585,0.000255469,0.00001677502,0.0003407616,0.00050766,0.0001304326,0.000006103548],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001292674,"about_ca_system_score_gemma":0.000006072758,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002532553,"about_ca_topic_score_gemma":0.000005408751,"domain_scores_codex":[0.9988492,0.00005174019,0.0001940017,0.0005375649,0.0001472782,0.0002202562],"domain_scores_gemma":[0.9988102,0.00005347532,0.00006587909,0.0009440734,0.00003569923,0.00009063778],"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":[3.366916e-7,0.00002160968,0.0001061572,0.00002072302,0.000004879253,0.000002332159,0.0002635977,0.7241554,0.0004911333,0.01588303,0.00008418712,0.2589666],"study_design_scores_gemma":[0.00008225415,0.00001111398,0.00004215746,0.00003655395,0.000004166926,0.00003068981,0.00001714269,0.9986566,0.00003256228,0.000849276,0.0001127514,0.0001246784],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07440238,0.0001784398,0.9244038,0.000304739,0.0001280411,0.000113623,0.000003375325,0.0003514323,0.0001142151],"genre_scores_gemma":[0.91517,0.000004084322,0.08447714,0.0001041447,0.0002081475,0.000001718393,0.00001878281,0.000009997103,0.000005956378],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8407676,"threshold_uncertainty_score":0.4337774,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03676392619399044,"score_gpt":0.264909366984472,"score_spread":0.2281454407904815,"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."}}