{"id":"W2048521160","doi":"10.1016/j.conengprac.2003.09.013","title":"A neuro-fuzzy system for looper tension control in rolling mills","year":2004,"lang":"en","type":"article","venue":"Control Engineering Practice","topic":"Metallurgy and Material Forming","field":"Engineering","cited_by":61,"is_retracted":false,"has_abstract":false,"ca_institutions":"Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Scrap; Control theory (sociology); Control engineering; Fuzzy logic; Fuzzy control system; Engineering; Rolling mill; Tension (geology); Controller (irrigation); Line (geometry); Control (management); Control system; Computer science; Mechanical engineering; Mathematics; Artificial intelligence; Materials science","routes":{"ca_aff":true,"ca_fund":true,"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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000627116,0.0002717793,0.0004248267,0.0001725379,0.00005572923,0.00007353789,0.0001464263,0.0001450189,0.000004205061],"category_scores_gemma":[0.0009548797,0.0002758912,0.00009661466,0.0001619586,0.000008219577,0.0005793251,0.0000121231,0.000254316,0.00004304517],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001710902,"about_ca_system_score_gemma":0.00002573387,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003598071,"about_ca_topic_score_gemma":0.000003819939,"domain_scores_codex":[0.9986617,0.00002766115,0.0004397647,0.000243697,0.0001485495,0.0004786012],"domain_scores_gemma":[0.9988347,0.0006612281,0.00006315271,0.0002453681,0.00008698259,0.0001085154],"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":[0.0001521062,0.00001811461,0.000002449929,0.0002636931,0.00006883023,0.00005446808,0.00007065786,0.9094302,0.08780012,0.001806378,0.00001800274,0.0003149532],"study_design_scores_gemma":[0.0081963,0.00008106328,0.00004993152,0.0003018257,0.0001627896,0.0001405727,0.00006506949,0.9608995,0.002195726,0.00003140657,0.02743806,0.0004377743],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01877643,0.0009523029,0.9747379,0.0003453875,0.002661366,0.001037708,0.00001844498,0.0008249652,0.0006454994],"genre_scores_gemma":[0.9947659,0.00003437425,0.004405109,0.0002322049,0.0002793685,0.0001732763,0.000005046759,0.00009188093,0.00001285489],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9759895,"threshold_uncertainty_score":0.9999693,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006009934490765423,"score_gpt":0.1990876773757197,"score_spread":0.1930777428849543,"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."}}