{"id":"W2044133977","doi":"10.1016/j.procir.2014.01.124","title":"Grouping Product Variants based on Alternate Machines for Each Operation","year":2014,"lang":"en","type":"article","venue":"Procedia CIRP","topic":"Product Development and Customization","field":"Business, Management and Accounting","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"","keywords":"Product (mathematics); Computer science; Computational biology; Engineering; Manufacturing engineering; Biology; Mathematics","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":[0.0007540898,0.0009038691,0.0008902094,0.003675396,0.0009948446,0.001600493,0.001337838,0.0005688751,0.003235606],"category_scores_gemma":[0.003375788,0.0004347397,0.001181378,0.003884583,0.001005938,0.001900556,0.001260749,0.0005888217,0.000966396],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007400178,"about_ca_system_score_gemma":0.001203412,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005328777,"about_ca_topic_score_gemma":0.005235314,"domain_scores_codex":[0.9983748,0.0002114057,0.0001485575,0.0004967077,0.0006507942,0.0001176768],"domain_scores_gemma":[0.9983789,0.0003103432,0.0002107509,0.0003851768,0.0006309123,0.00008391483],"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":[0.0005858893,0.0001656954,0.02032999,0.0007149304,0.0002183891,0.0008164551,0.001341981,0.1049668,0.04275792,0.03423305,0.006499726,0.7873691],"study_design_scores_gemma":[0.0000782168,0.0006722873,0.03061212,0.000134216,0.0003687946,0.002431804,0.00169682,0.8037074,0.04983723,0.04852175,0.06160347,0.0003358861],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08131421,0.00037947,0.9096709,0.0001065066,0.00009597634,0.0004035797,0.0005211907,0.001216474,0.006291624],"genre_scores_gemma":[0.2650569,0.0002367569,0.729572,0.00001997958,0.00002434325,0.0002441259,0.001188722,0.0001964687,0.003460702],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005328777,"threshold_uncertainty_score":0.0108242,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01260367878760567,"score_gpt":0.2144035378554539,"score_spread":0.2017998590678482,"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."}}