{"id":"W4318262335","doi":"10.1016/b978-0-32-399163-6.00011-1","title":"Artificial intelligence models in digital twins for health and well-being","year":2023,"lang":"en","type":"book-chapter","venue":"Elsevier eBooks","topic":"Digital Transformation in Industry","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"Preparedness; Scope (computer science); Health care; Field (mathematics); Domain (mathematical analysis); Computer science; Digital health; Data science; Artificial intelligence; Risk analysis (engineering); Medicine; Political science","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"],"consensus_categories":[],"category_scores_codex":[0.0001443605,0.0003186699,0.0003869279,0.0002628992,0.00004532966,0.0001713843,0.0001502681,0.0002743701,0.00000789261],"category_scores_gemma":[0.00001045337,0.00036619,0.00009777136,0.0000241222,0.00006316812,0.0002856059,0.00003718748,0.0004268488,0.00009063094],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00012148,"about_ca_system_score_gemma":0.00006717544,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":1.853972e-7,"about_ca_topic_score_gemma":0.00001374685,"domain_scores_codex":[0.9985352,0.000002350217,0.0006840809,0.0002574083,0.0001796905,0.0003413234],"domain_scores_gemma":[0.9994614,0.0001012754,0.00006034599,0.0001975938,0.00002959426,0.0001497551],"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":[0.000005370102,0.000002101009,5.574886e-7,0.0003905043,0.00002485281,0.000003733887,0.0009301713,0.00270319,2.583811e-7,0.09805892,0.00005090318,0.8978294],"study_design_scores_gemma":[0.000074547,0.00006290252,4.362974e-7,0.001293608,0.00001062731,0.000009052339,0.0001407405,0.01615368,0.00004180775,0.7270154,0.2545999,0.0005973251],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.0000466199,0.0001433977,0.003436461,0.00004987282,0.0003879773,0.0006930815,0.000122335,0.0003101352,0.9948101],"genre_scores_gemma":[0.03726538,0.0003527312,0.000606941,0.0002408085,0.0004301543,0.0002131006,0.000214933,0.0004348098,0.9602411],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.8972321,"threshold_uncertainty_score":0.999879,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04022501631924048,"score_gpt":0.261020022150785,"score_spread":0.2207950058315445,"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."}}