{"id":"W4389722732","doi":"10.1109/mie.2023.3322884","title":"Table of Contents","year":2023,"lang":"en","type":"article","venue":"IEEE Industrial Electronics Magazine","topic":"Engineering and Technology Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Nanjing University; Universidad de Zaragoza; Università degli Studi di Salerno; Universidade de Vigo; Nanjing University of Posts and Telecommunications; Danmarks Tekniske Universitet; Università di Catania; Università degli Studi di Pavia; Technische Universiteit Delft; Aalborg Universitet; Politechnika Warszawska; Harbin Institute of Technology; Swinburne University of Technology; Griffith University; Universitatea Tehnică „Gheorghe Asachi” din Iaşi; Università degli Studi di Padova; Universidade de Lisboa; École de technologie supérieure; City University of Hong Kong; Keio University","keywords":"Table (database); Computer science; Database","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001272558,0.000111,0.0001763815,0.0002611578,0.00002487514,0.000006858819,0.0001541611,0.0002119128,0.00002249764],"category_scores_gemma":[0.00006943663,0.0001223943,0.00003156828,0.001506279,0.00002796683,0.00005255162,0.00001219399,0.0004154775,0.0001501597],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004411208,"about_ca_system_score_gemma":0.00003456198,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003059981,"about_ca_topic_score_gemma":0.000006054085,"domain_scores_codex":[0.9991912,0.000005033501,0.0002447687,0.00009840892,0.000106424,0.0003541453],"domain_scores_gemma":[0.9996512,0.00003745903,0.00002858156,0.0002021508,0.00005292468,0.00002767263],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00001885413,0.00004805829,0.0007857051,0.00005028243,0.0002921414,0.00001580766,0.00003234729,0.1601717,0.5516614,0.01711484,0.2543121,0.01549681],"study_design_scores_gemma":[0.002837899,0.0003080035,0.0003993693,0.00008232098,0.00005851939,0.00001844943,0.00001910291,0.06835575,0.5709236,0.002324616,0.3541042,0.0005681802],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9845238,0.0003461782,0.002448427,0.0003605383,0.001889616,0.0002498541,0.00005490346,0.002976515,0.007150139],"genre_scores_gemma":[0.9985644,0.0001254098,0.0000563638,0.000006739285,0.0001351898,0.00002124297,0.0000317726,0.00003361662,0.0010253],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09979209,"threshold_uncertainty_score":0.4991097,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03054555579587637,"score_gpt":0.22996757195503,"score_spread":0.1994220161591537,"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."}}