{"id":"W2955751796","doi":"10.1016/j.eng.2019.07.001","title":"New Trends in Intelligent Manufacturing","year":2019,"lang":"en","type":"article","venue":"Engineering","topic":"Manufacturing Process and Optimization","field":"Engineering","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada","funders":"","keywords":"Manufacturing engineering; Engineering; Computer science; Business","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00004126133,0.000134103,0.0001224845,0.0002836897,0.000006251228,0.00002817516,0.00009872012,0.00005426957,0.0006358739],"category_scores_gemma":[0.000002183095,0.0001457289,0.00003142803,0.0001331315,0.00000107004,0.0001296118,0.00001803569,0.0001507453,0.00009529906],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000680872,"about_ca_system_score_gemma":0.000002779531,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000014959,"about_ca_topic_score_gemma":0.0000042068,"domain_scores_codex":[0.9994161,0.000001571108,0.0001497514,0.0001270067,0.00008305025,0.0002225464],"domain_scores_gemma":[0.9997804,0.00001118295,0.000008693662,0.0001362593,0.000002398978,0.0000610697],"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":[0.000001021018,0.000001752607,0.0001897974,0.00005070017,0.000005656252,0.000001996991,0.0001189325,0.963613,0.0002006331,0.00004248958,0.00009616154,0.03567788],"study_design_scores_gemma":[0.0002163382,0.000009122119,0.006915027,0.00005806165,0.000002556915,0.000002805223,0.00001088492,0.9068524,0.07256387,0.00001778654,0.01309774,0.0002533841],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6785561,0.0004557942,0.3093295,0.00002966904,0.00123441,0.0001207418,0.000001098686,0.000863302,0.00940932],"genre_scores_gemma":[0.9939737,0.00003169262,0.004723447,0.000005886211,0.00007279802,0.000004291614,0.000006634426,0.00003974184,0.00114181],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3154176,"threshold_uncertainty_score":0.6962373,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0052319616344135,"score_gpt":0.185263762521674,"score_spread":0.1800318008872605,"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."}}