{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","research_integrity"],"consensus_categories":["research_integrity"],"category_scores_codex":[0.0004902566,0.000697711,0.0006880998,0.0008311082,0.0008144483,0.0003068804,0.0009154026,0.001549234,0.00006014767],"category_scores_gemma":[0.000204134,0.0006281572,0.0005880251,0.001549565,0.0005022968,0.0002792446,0.00002030215,0.004327492,0.0001833094],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004529969,"about_ca_system_score_gemma":0.0007728464,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001469793,"about_ca_topic_score_gemma":0.002709699,"domain_scores_codex":[0.9961767,0.00004539114,0.001071972,0.0008753928,0.0009286873,0.0009018317],"domain_scores_gemma":[0.9966182,0.0008987617,0.0006720102,0.0007884416,0.001001066,0.0000215461],"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":[0.000382339,0.0003758943,0.000002380611,0.0002250394,0.0004302316,0.000001439377,0.00003010909,0.001246295,0.0002635281,0.009344973,0.977808,0.009889781],"study_design_scores_gemma":[0.0003831152,0.0002568165,6.118312e-7,0.0001877235,0.0009410339,0.000002296204,0.00004971723,0.003439093,0.003581971,0.0035463,0.9870255,0.0005858114],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"editorial","genre_gemma":"editorial","genre_scores_codex":[0.001142451,0.000233572,0.01169235,0.001351156,0.9833859,0.001215087,0.0002926098,0.0003590842,0.0003277485],"genre_scores_gemma":[0.04470669,0.0002019304,0.00003676899,0.0002131335,0.9540747,0.0001268248,0.0002024115,0.0001625969,0.0002749719],"genre_candidate":"editorial","genre_consensus":"editorial","teacher_disagreement_score":0.04356424,"threshold_uncertainty_score":0.999747,"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."}}