{"id":"W3207034280","doi":"10.12688/digitaltwin.17475.1","title":"Digital twins for well-being: an overview","year":2021,"lang":"en","type":"article","venue":"Digital Twin","topic":"Digital Transformation in Industry","field":"Engineering","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Research Council Canada","keywords":"Scope (computer science); Architecture; Computer science; Data science; Geography","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001767678,0.0005890235,0.0003581236,0.00389673,0.002270671,0.007420402,0.00094014,0.002314314,0.01307823],"category_scores_gemma":[0.001612703,0.0002769436,0.0005563643,0.00445492,0.004217783,0.00980158,0.005851189,0.002972762,0.002642079],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004467163,"about_ca_system_score_gemma":0.003345631,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002729908,"about_ca_topic_score_gemma":0.00365326,"domain_scores_codex":[0.998676,0.000482734,0.0001085572,0.0001346667,0.0004371659,0.0001608448],"domain_scores_gemma":[0.9991004,0.0004260119,0.00006292814,0.00005716208,0.00018667,0.0001668801],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00001793674,0.00003517981,0.0004539398,0.0008860992,0.000008648284,0.0001557326,0.002548455,0.0003240643,0.0002785513,0.7615164,0.01591918,0.2178558],"study_design_scores_gemma":[0.000002148111,0.00003428859,0.0009414598,0.001622515,0.00001004088,0.0006573703,0.003729478,0.0004581488,0.000421441,0.07826984,0.913836,0.00001724273],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"other","genre_gemma":"review","genre_scores_codex":[0.01261634,0.243079,0.05581439,0.03165222,0.002233419,0.0001395499,0.0002116059,0.000477579,0.653776],"genre_scores_gemma":[0.3361315,0.5123287,0.05224933,0.01104348,0.001870099,0.0003428861,0.0007471515,0.0004495065,0.08483728],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.01307823,"threshold_uncertainty_score":0.04375106,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03214502571413023,"score_gpt":0.2594531770196271,"score_spread":0.2273081513054969,"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."}}