{"id":"W2310184056","doi":"","title":"Minimization of Production Cost by Reducing Casting Defects Using Dmaic Approach","year":2012,"lang":"en","type":"article","venue":"Mechanical Engineering Research","topic":"Quality and Supply Management","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"DMAIC; Casting; Production (economics); Computer science; Reduction (mathematics); Manufacturing engineering; Process engineering; Reliability engineering; Engineering; Six Sigma; Materials science; Lean manufacturing; Metallurgy; Mathematics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004025892,0.0006026912,0.0006666702,0.001837847,0.000437191,0.001088599,0.001056855,0.0003498569,0.00179461],"category_scores_gemma":[0.0007261,0.0001941559,0.0004561809,0.001020323,0.0002830604,0.0004606076,0.0004828861,0.0004275259,0.0003938599],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008423172,"about_ca_system_score_gemma":0.00115214,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001880384,"about_ca_topic_score_gemma":0.002728004,"domain_scores_codex":[0.9994412,0.00005442865,0.00002306028,0.00007822739,0.0003283532,0.00007461079],"domain_scores_gemma":[0.9996043,0.00006813815,0.00009076431,0.00005394172,0.0001617371,0.00002121111],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0002846438,0.0003742411,0.005273598,0.0006206252,0.00008915264,0.0002713258,0.0001560206,0.2761255,0.1654715,0.03879209,0.002770057,0.5097712],"study_design_scores_gemma":[0.00005090109,0.0006260633,0.004718625,0.00006481857,0.000166175,0.0005676074,0.0001745433,0.8349097,0.1277764,0.008356512,0.02254406,0.00004455514],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09933355,0.001366887,0.8708919,0.0002685743,0.00006212193,0.0001365598,0.0001017469,0.0009690339,0.02686968],"genre_scores_gemma":[0.7443286,0.0006823619,0.2471534,0.00006446143,0.00004360119,0.00009281038,0.0001630564,0.0001082791,0.007363541],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001880384,"threshold_uncertainty_score":0.006111503,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1045405722563709,"score_gpt":0.3131161935363053,"score_spread":0.2085756212799343,"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."}}