{"id":"W4391892432","doi":"10.1109/mnet.2024.3366560","title":"A Revolution of Personalized Healthcare: Enabling Human Digital Twin With Mobile AIGC","year":2024,"lang":"en","type":"article","venue":"IEEE Network","topic":"Digital Transformation in Industry","field":"Engineering","cited_by":103,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo; Concordia University","funders":"National Natural Science Foundation of China","keywords":"Computer science; Health care; Mobile computing; Computer network; Mobile telephony; Computer security; Internet privacy; Mobile radio","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":[0.0007395039,0.0003858155,0.0003023317,0.0005076042,0.000452334,0.001913158,0.0009694568,0.001252691,0.003230637],"category_scores_gemma":[0.001595787,0.0001800182,0.0002774434,0.0006340466,0.0007153596,0.002440474,0.002629626,0.001073076,0.001261321],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004848252,"about_ca_system_score_gemma":0.000692987,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001005373,"about_ca_topic_score_gemma":0.001087889,"domain_scores_codex":[0.999473,0.0001783844,0.00002612203,0.0000886011,0.0001637054,0.00007019787],"domain_scores_gemma":[0.99945,0.0001617022,0.00003927272,0.0001361826,0.0001130865,0.00009972914],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0005754457,0.0002817445,0.005892442,0.0005843178,0.00009261487,0.002014381,0.003088996,0.01770519,0.04324043,0.1933311,0.04772307,0.6854702],"study_design_scores_gemma":[0.0001153549,0.0006992253,0.002765234,0.0003095334,0.0001510296,0.004934034,0.001572466,0.298208,0.03915278,0.1285661,0.523365,0.0001611659],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.04065212,0.002684353,0.8855149,0.008112447,0.0008062538,0.0003608257,0.0002801136,0.005342504,0.0562465],"genre_scores_gemma":[0.6796818,0.002879394,0.2953014,0.004127584,0.0005701136,0.0002701554,0.0005540382,0.0003808404,0.01623475],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.003230637,"threshold_uncertainty_score":0.01080751,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01715056876893639,"score_gpt":0.2451450655801544,"score_spread":0.227994496811218,"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."}}