{"id":"W2116158268","doi":"10.5539/jel.v3n3p172","title":"Enhancing Manufacturing Process Education via Computer Simulation and Visualization","year":2014,"lang":"en","type":"article","venue":"Journal of Education and Learning","topic":"Metallurgy and Material Forming","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Visualization; Process (computing); Computer science; Schedule; Manufacturing engineering; Industrial engineering; Engineering drawing; Engineering; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003127493,0.00006364126,0.000093538,0.0001290073,0.00009275579,0.00006054121,0.00002249902,0.00003651291,0.00002434489],"category_scores_gemma":[0.00005121913,0.00006051504,0.00001260427,0.000038443,0.000006793728,0.0003327704,0.000004909342,0.000117178,0.000001564924],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001815822,"about_ca_system_score_gemma":0.00003060217,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002071961,"about_ca_topic_score_gemma":7.600363e-7,"domain_scores_codex":[0.9995608,0.00004252902,0.0002137182,0.00005217554,0.00006874793,0.0000619829],"domain_scores_gemma":[0.9996769,0.00004849953,0.0001230332,0.00002582762,0.00007309803,0.00005267626],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001346914,0.00004954022,0.001062489,0.0005034222,0.00002393517,1.211634e-7,0.005753489,0.2716576,0.01205084,0.0004709346,0.00002681711,0.7083873],"study_design_scores_gemma":[0.0005343137,0.0002392161,0.02809242,0.0008330128,0.00008840652,0.0001823984,0.002518027,0.8947932,0.03645741,0.001540572,0.03428199,0.0004390483],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8127172,0.0001060208,0.1860744,0.0000143098,0.0008023562,0.00003051304,1.459397e-8,0.00001786049,0.0002373415],"genre_scores_gemma":[0.9975339,0.00002801763,0.001753866,0.00004351018,0.0005504243,0.000001121179,0.000002903491,0.00001084384,0.00007544766],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7079483,"threshold_uncertainty_score":0.2467732,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005525331581142941,"score_gpt":0.2722630790255927,"score_spread":0.2667377474444498,"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."}}