{"id":"W4416078238","doi":"10.1109/mce.2025.3588306","title":"Physical Artificial Intelligence in Consumer Electronics","year":2025,"lang":"en","type":"article","venue":"IEEE Consumer Electronics Magazine","topic":"Artificial Intelligence Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Custom Security Industries (Canada); Wilfrid Laurier University; Huawei Technologies (Canada); University of Ottawa","funders":"","keywords":"Electronics; Generative grammar; Perception; Applications of artificial intelligence; Technology forecasting; Ambient intelligence","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":[0.001246764,0.00032082,0.000260215,0.0006443549,0.001255303,0.0032137,0.0005454347,0.002154407,0.01114668],"category_scores_gemma":[0.001879395,0.0002758682,0.0002071299,0.0007803753,0.003757493,0.003993105,0.001473185,0.002701797,0.002718596],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001769037,"about_ca_system_score_gemma":0.0008150486,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001597502,"about_ca_topic_score_gemma":0.001799545,"domain_scores_codex":[0.999169,0.0002646609,0.0000270791,0.00008791083,0.0003950553,0.0000563316],"domain_scores_gemma":[0.9992571,0.0004094545,0.00002402745,0.00007373893,0.0001809106,0.00005460344],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002131306,0.00003552093,0.00034194,0.0001844174,0.000009172394,0.0001607527,0.0004221455,0.001322984,0.0007494627,0.7796641,0.1016566,0.1154315],"study_design_scores_gemma":[0.000007623659,0.00003245131,0.0004153328,0.0001964327,0.000003959473,0.0002132706,0.0002346364,0.00245671,0.0006320621,0.2705048,0.7252856,0.00001721362],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.008426388,0.09200089,0.07271053,0.09273002,0.005804506,0.00007004262,0.00008722642,0.0005884725,0.7275819],"genre_scores_gemma":[0.4080215,0.07691553,0.0650091,0.02746987,0.004891361,0.0002409249,0.0001876579,0.00038703,0.416877],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01114668,"threshold_uncertainty_score":0.03728938,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02112004914974261,"score_gpt":0.3096860055122052,"score_spread":0.2885659563624626,"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."}}