{"id":"W2095271244","doi":"10.1016/j.conengprac.2009.05.006","title":"An adaptive system for modelling and simulation of electrical arc furnaces","year":2009,"lang":"en","type":"article","venue":"Control Engineering Practice","topic":"Neural Networks and Applications","field":"Computer Science","cited_by":38,"is_retracted":false,"has_abstract":false,"ca_institutions":"Toronto Metropolitan University","funders":"Ontario Centres of Excellence","keywords":"Arc (geometry); Electric arc; Computer science; Engineering; Mechanical engineering; Physics; Electrode","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003256888,0.0004156049,0.000486989,0.0002987643,0.0003680273,0.0005169035,0.0008254431,0.00108071,0.001948848],"category_scores_gemma":[0.0014232,0.000285294,0.0003490938,0.0002895104,0.0003897376,0.0004657764,0.0004962126,0.0006945762,0.0002275245],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004927431,"about_ca_system_score_gemma":0.0005855157,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009738136,"about_ca_topic_score_gemma":0.006037598,"domain_scores_codex":[0.9998424,0.00005450167,0.00001150269,0.00003405518,0.00004456585,0.00001286973],"domain_scores_gemma":[0.9997026,0.0001605647,0.00003092778,0.00002970882,0.00006235452,0.00001378054],"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":[0.00002548459,0.00001121333,0.0001786535,0.00001674192,0.000007932145,0.00002023106,0.00001986465,0.9921592,0.001301332,0.001208215,0.00008000425,0.004971172],"study_design_scores_gemma":[0.00000330741,0.000006729373,0.00003921772,9.280288e-7,0.000001929222,0.000002301202,0.000001317714,0.9993827,0.0002258529,0.0001937882,0.0001406283,0.000001277682],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1187847,0.0002632194,0.8720439,0.0002300226,0.0001042558,0.0001041351,0.0001512025,0.001605711,0.006712879],"genre_scores_gemma":[0.9492231,0.0001167158,0.04814644,0.00002975882,0.00001589231,0.0001296891,0.00008681632,0.00004159229,0.002210022],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009738136,"threshold_uncertainty_score":0.01936293,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01533924439866584,"score_gpt":0.2573047962677882,"score_spread":0.2419655518691224,"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."}}