{"id":"W4396243243","doi":"10.1109/tce.2024.3357856","title":"Guest Editorial of the Special Section on Neural Computing-Driven Artificial Intelligence for Consumer Electronics","year":2024,"lang":"en","type":"editorial","venue":"IEEE Transactions on Consumer Electronics","topic":"E-commerce and Technology Innovations","field":"Business, Management and Accounting","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Special section; Electronics; Section (typography); Artificial neural network; Computer science; Artificial intelligence; Electrical engineering; Engineering; Telecommunications; Engineering physics; Operating system","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":[0.002992112,0.002879414,0.002515503,0.002532896,0.002266383,0.006114088,0.002816446,0.01025732,0.0159887],"category_scores_gemma":[0.009051003,0.0007878529,0.002037841,0.001162859,0.001773429,0.004175391,0.001250217,0.01449313,0.01289317],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002040407,"about_ca_system_score_gemma":0.001748066,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009581983,"about_ca_topic_score_gemma":0.002951793,"domain_scores_codex":[0.9974428,0.0002908991,0.0002769998,0.0003805505,0.001415837,0.0001929134],"domain_scores_gemma":[0.9923667,0.002408932,0.0004419235,0.0001738708,0.003226542,0.001382029],"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":[0.00003167225,0.00001567881,0.00002926155,0.0001674317,0.00001032476,0.0001372823,0.000008187277,0.00004329459,0.00009596304,0.0004282932,0.9927684,0.00626419],"study_design_scores_gemma":[0.00003398094,0.00003306742,0.000219894,0.0002438463,0.0000262189,0.000394757,0.000022266,0.0002816003,0.0001704848,0.00120565,0.9973506,0.00001760908],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"editorial","genre_gemma":"editorial","genre_scores_codex":[0.00004335205,0.005144233,0.0002197148,0.0206479,0.9720616,0.00001462217,0.00003771207,0.00004781326,0.001783039],"genre_scores_gemma":[0.0003546468,0.00433281,0.0001105626,0.009782229,0.9779087,0.00001388557,0.00002497314,0.00003436391,0.007437876],"genre_candidate":"editorial","genre_consensus":"editorial","teacher_disagreement_score":0.0159887,"threshold_uncertainty_score":0.05348754,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01720674062426247,"score_gpt":0.2637654056954484,"score_spread":0.246558665071186,"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."}}