{"id":"W4286808944","doi":"10.1109/tase.2019.2903614","title":"IEEE Transactions on Automation Science and Engineering","year":2019,"lang":"en","type":"article","venue":"IEEE Transactions on Automation Science and Engineering","topic":"Advanced Manufacturing and Logistics Optimization","field":"Engineering","cited_by":37,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Centro de Investigación y de Estudios Avanzados del Instituto Politécnico Nacional; University of Illinois at Urbana-Champaign; Peking University; Korea Advanced Institute of Science and Technology; University of Tsukuba; Leibniz-Gemeinschaft; National Institute of Advanced Industrial Science and Technology; National Tsing Hua University; Shanghai Jiao Tong University; Tsinghua University; University of Waterloo; Università degli Studi di Salerno; Rensselaer Polytechnic Institute; National University of Singapore; Gottfried Wilhelm Leibniz Universität Hannover; University of Hong Kong; Korea University; Utah State University; Chinese Academy of Sciences; Keio University; University of Toronto; Harbin Institute of Technology; University of Technology Sydney; Sun Yat-sen University; Cardiff University; University of Connecticut; Universidade de Macau; South China University of Technology; University of Wisconsin-Madison; McGill University","keywords":"Automation; Engineering; Manufacturing engineering; Computer science; Systems engineering; Software engineering; Engineering management; Mechanical engineering","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001017912,0.000872689,0.001238297,0.001222166,0.0006393825,0.002536636,0.0007410372,0.001442145,0.03040941],"category_scores_gemma":[0.001992503,0.0002478174,0.0006148718,0.001684474,0.0007321785,0.001234748,0.0007380361,0.001072676,0.01052393],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005642879,"about_ca_system_score_gemma":0.001127133,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002884672,"about_ca_topic_score_gemma":0.004517457,"domain_scores_codex":[0.9990603,0.0001655589,0.00007300001,0.0001006498,0.0005095826,0.00009078926],"domain_scores_gemma":[0.9982209,0.0002639688,0.00005368439,0.0003671921,0.001019817,0.00007453987],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002700578,0.0002263225,0.00178054,0.0004780605,0.0001480289,0.0002793768,0.0001122928,0.01620983,0.01062476,0.04228643,0.126615,0.8009692],"study_design_scores_gemma":[0.00003024552,0.0003691131,0.005942025,0.0002167222,0.000195398,0.000858406,0.0002875471,0.09195746,0.01117735,0.04922193,0.839677,0.000066801],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.02729866,0.03514926,0.5430934,0.007890469,0.05237744,0.0002020266,0.0008854863,0.001813303,0.33129],"genre_scores_gemma":[0.3992396,0.03168487,0.1103096,0.001916006,0.005775443,0.000188256,0.002067227,0.0004231199,0.4483958],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.9695906,"threshold_uncertainty_score":0.1017296,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008798368232731417,"score_gpt":0.2157518632101376,"score_spread":0.2069534949774061,"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."}}