{"id":"W4312050794","doi":"10.1109/mie.2022.3212608","title":"Table of Contents","year":2022,"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; 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":[0.0001376349,0.0001029151,0.0001676075,0.0001769004,0.00006469529,0.00000490096,0.0002041888,0.00009190219,0.0001359782],"category_scores_gemma":[0.00003031237,0.0001248118,0.00003243264,0.0008105139,0.00002219199,0.00004029202,0.00002776995,0.000723388,0.0000119125],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001168208,"about_ca_system_score_gemma":0.00005022593,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004725269,"about_ca_topic_score_gemma":0.000003676381,"domain_scores_codex":[0.9992118,0.00001090095,0.000244098,0.00009901873,0.0001453129,0.0002888173],"domain_scores_gemma":[0.9996752,0.00002543113,0.0000385425,0.0002019099,0.00003611998,0.00002280192],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00003674184,0.0001300695,0.0005518692,0.00002282022,0.0002649248,0.00001194373,0.00003792683,0.5003527,0.3448195,0.02171928,0.1224835,0.009568729],"study_design_scores_gemma":[0.002720876,0.0005722626,0.00006602342,0.00001482801,0.0000528566,0.00005344198,0.00003286075,0.03043702,0.2028172,0.001329868,0.7614435,0.0004592885],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9790283,0.001258453,0.004175971,0.0004068369,0.002851476,0.0003770684,0.0001510472,0.001299707,0.01045118],"genre_scores_gemma":[0.9990119,0.00002757528,0.00007870963,0.00001468797,0.00008554015,0.00005500989,0.00002567581,0.0000293246,0.0006715291],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.63896,"threshold_uncertainty_score":0.5089679,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02177478126331125,"score_gpt":0.2102453591932635,"score_spread":0.1884705779299523,"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."}}