{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00270799,0.0007865802,0.0007568576,0.00233034,0.0008018391,0.003646785,0.001495928,0.002931468,0.01335499],"category_scores_gemma":[0.004090923,0.0002772081,0.0007545638,0.00225265,0.003228854,0.007410334,0.001695381,0.004444943,0.00395716],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002087181,"about_ca_system_score_gemma":0.001556199,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006394415,"about_ca_topic_score_gemma":0.001048383,"domain_scores_codex":[0.9981189,0.0004101644,0.0001117336,0.0002745333,0.0009303968,0.0001542532],"domain_scores_gemma":[0.9959486,0.001829316,0.000228205,0.0003534075,0.001285132,0.0003554323],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00006035946,0.0001178145,0.0007222142,0.001182806,0.00003902689,0.0001863953,0.0004301965,0.001065056,0.001403537,0.6732667,0.06427272,0.2572533],"study_design_scores_gemma":[0.00001188002,0.00007351435,0.0005145922,0.0004155948,0.00001387279,0.0003755227,0.0002444563,0.001851993,0.0005424244,0.1311556,0.8647747,0.00002575035],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.007002427,0.5315855,0.07173926,0.08771984,0.01399532,0.00007928306,0.0002065728,0.0005473818,0.2871245],"genre_scores_gemma":[0.1491338,0.6129448,0.07633439,0.03602639,0.03038301,0.0002349704,0.0005467405,0.0002883259,0.0941076],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01335499,"threshold_uncertainty_score":0.0446769,"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."}}