{"id":"W4387665640","doi":"10.1109/icac57885.2023.10275163","title":"Keynote Presentation of ICAC2023","year":2023,"lang":"en","type":"article","venue":"","topic":"Digital Transformation in Industry","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Economic and Social Research Council; Engineering and Physical Sciences Research Council; National Natural Science Foundation of China; Natural Sciences and Engineering Research Council of Canada; European Commission; Ministry of Education of the People's Republic of China; Department for Environment, Food and Rural Affairs, UK Government; National Science Foundation","keywords":"Smart manufacturing; Manufacturing; Manufacturing engineering; Presentation (obstetrics); Product (mathematics); Advanced manufacturing; China; Computer-integrated manufacturing; Industry 4.0; Process development execution system; Engineering; New product development; Computer science; Business; Engineering management; Political science; Marketing","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.001354337,0.001806244,0.0008405713,0.001779606,0.003613961,0.007246338,0.001125278,0.006762503,0.1995055],"category_scores_gemma":[0.002717902,0.000322183,0.0008704939,0.001500386,0.0006157922,0.002361464,0.001765481,0.006232812,0.1477782],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003358174,"about_ca_system_score_gemma":0.002526197,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007827586,"about_ca_topic_score_gemma":0.01550392,"domain_scores_codex":[0.9991311,0.00009631043,0.0000396488,0.0001542283,0.0004242649,0.0001543778],"domain_scores_gemma":[0.9986475,0.0002085562,0.00006389977,0.00006717042,0.0007048378,0.0003079458],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00003655422,0.00001507682,0.00002676918,0.00004487991,0.000001948931,0.00007496699,0.00001611555,0.00002637026,0.0001551342,0.001060328,0.9923033,0.006238688],"study_design_scores_gemma":[0.000007682036,0.00001409781,0.0002297291,0.00005974061,0.000002708156,0.00003630491,0.00003676412,0.00007204225,0.000108786,0.0003207035,0.9991048,0.000006516042],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.001095023,0.01162041,0.001274852,0.05492006,0.3595589,0.0004961782,0.003352729,0.0008190396,0.5668628],"genre_scores_gemma":[0.005399268,0.003347094,0.0004252338,0.01387598,0.05757587,0.0002088384,0.001442107,0.0002998917,0.9174258],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.1995055,"threshold_uncertainty_score":0.6674125,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02723023263926128,"score_gpt":0.2538855880260067,"score_spread":0.2266553553867455,"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."}}