{"id":"W2533324395","doi":"10.1109/icccas.2002.1178996","title":"A rough neural network for material proportioning system","year":2003,"lang":"en","type":"article","venue":"","topic":"Rough Sets and Fuzzy Logic","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Regina","funders":"","keywords":"Artificial neural network; Rough set; Computer science; Artificial intelligence; Function (biology); Raw data; Backpropagation; Raw material; Data mining; Control (management); Pattern recognition (psychology); Machine learning","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":[0.0005787652,0.0004868066,0.0007149956,0.0004925122,0.0004471852,0.0008301194,0.0008145199,0.001083082,0.002296174],"category_scores_gemma":[0.001434481,0.0003071422,0.0005920708,0.0004169299,0.0004330994,0.0008955576,0.0004052965,0.0007810523,0.0006377149],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005969026,"about_ca_system_score_gemma":0.000583737,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003215944,"about_ca_topic_score_gemma":0.002302796,"domain_scores_codex":[0.9996131,0.0001023906,0.00002230804,0.00007669152,0.0001552465,0.00003032071],"domain_scores_gemma":[0.9997883,0.00008049697,0.00002462736,0.00002070022,0.00007714882,0.000008672002],"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":[0.0001102839,0.00002830833,0.0003116256,0.0001276004,0.0000400198,0.0001091092,0.00005711507,0.8843576,0.01235544,0.01001268,0.0010327,0.09145746],"study_design_scores_gemma":[0.000005029318,0.00002050323,0.00007691071,0.000006228677,0.000008040675,0.00002014957,0.000003047278,0.9961068,0.001104725,0.00196723,0.0006733801,0.000007922346],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0114794,0.0004205467,0.9846659,0.0001420875,0.00006502138,0.00004580798,0.00005088875,0.0005770794,0.002553206],"genre_scores_gemma":[0.6181819,0.0007191132,0.3741345,0.0001435636,0.00007829388,0.0002822936,0.0001976177,0.00006007679,0.006202685],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003215944,"threshold_uncertainty_score":0.007681489,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01935136010147676,"score_gpt":0.2268575248627441,"score_spread":0.2075061647612673,"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."}}