{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008825397,0.0001275052,0.0001531861,0.00006198931,0.00004255577,0.00009864782,0.00008223508,0.00008896908,0.00001635818],"category_scores_gemma":[0.000001816355,0.0001190837,0.00005740816,0.0004175297,0.00005214001,0.0004785014,0.000004978459,0.0002200955,0.00002639333],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008702329,"about_ca_system_score_gemma":0.00002903186,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008427011,"about_ca_topic_score_gemma":0.000005366273,"domain_scores_codex":[0.9991701,0.000008256669,0.0002577228,0.0001254984,0.0001905042,0.0002479328],"domain_scores_gemma":[0.9997101,0.00004229417,0.00002016485,0.0001296385,0.00003372695,0.00006412116],"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":[0.00005804612,0.00004141707,0.0007305018,0.002070883,0.0002541466,0.00003275307,0.001815391,0.9078031,0.0005272232,0.005619105,0.06567933,0.0153681],"study_design_scores_gemma":[0.001813492,0.0008904778,0.0004536388,0.007218852,0.0001227624,0.0001860759,0.001245038,0.04277012,0.003040208,0.005925841,0.9347448,0.001588638],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7915467,0.01865433,0.03042374,0.0002019697,0.008720351,0.001503769,0.0002506573,0.003744276,0.1449542],"genre_scores_gemma":[0.9982327,0.00004193779,0.0001125514,0.00001519055,0.001082341,0.0000505662,0.00003121133,0.00004212918,0.000391338],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8690655,"threshold_uncertainty_score":0.4856091,"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."}}