{"id":"W3010664460","doi":"10.3390/met10030360","title":"Optimization of Industrial Casting Processes","year":2020,"lang":"en","type":"article","venue":"Metals","topic":"Metallurgical Processes and Thermodynamics","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Casting; Process (computing); Process engineering; Manufacturing engineering; Computer science; Continuous casting; Process development; Metallurgy; Industrial engineering; Materials science; Mechanical engineering; Engineering","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":[0.0006182643,0.0006998802,0.0007999929,0.0006903046,0.0004917434,0.001324499,0.000578641,0.0005132205,0.002543796],"category_scores_gemma":[0.00129827,0.0003177659,0.0004120264,0.0007991181,0.0003164228,0.0004370514,0.0004540363,0.0006309957,0.0007142244],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008019311,"about_ca_system_score_gemma":0.00106244,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001639194,"about_ca_topic_score_gemma":0.001966448,"domain_scores_codex":[0.9993684,0.00009461593,0.0000256452,0.00009752333,0.0003226372,0.00009129599],"domain_scores_gemma":[0.9997721,0.00007274646,0.00003617786,0.0000347872,0.00007342373,0.0000106703],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0003681356,0.0002409807,0.001792217,0.0006973413,0.00005165737,0.0001053127,0.00007076459,0.7656646,0.08529377,0.008699953,0.001792422,0.1352227],"study_design_scores_gemma":[0.00008893016,0.0005289885,0.003351176,0.00006870123,0.00006696163,0.00007560257,0.00006310978,0.8750771,0.09837519,0.004376939,0.01789386,0.00003340076],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4627291,0.008850246,0.4434547,0.0005178503,0.0002836703,0.0003739513,0.000790512,0.002401525,0.08059832],"genre_scores_gemma":[0.9384095,0.001912008,0.05637436,0.00003370637,0.00002776481,0.0001225692,0.000391259,0.0002358382,0.002492941],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002543796,"threshold_uncertainty_score":0.008509874,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05313222357028582,"score_gpt":0.2220348528571828,"score_spread":0.168902629286897,"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."}}