{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.00003896966,0.000220803,0.0002046895,0.00006119789,0.00004345178,0.001165425,0.0001942981,0.0001205523,0.0001110755],"category_scores_gemma":[0.00005316535,0.0002460013,0.0001560549,0.0002561206,0.00003357587,0.003727656,0.00003110229,0.0001363198,0.0003653512],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005898138,"about_ca_system_score_gemma":0.00003855069,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":1.945451e-7,"about_ca_topic_score_gemma":8.114371e-7,"domain_scores_codex":[0.9988757,0.000003646617,0.0003363341,0.0002242512,0.0002030236,0.0003570861],"domain_scores_gemma":[0.9993213,0.00007322527,0.00002079582,0.0003177105,0.00008334869,0.0001836392],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00005381948,0.0009637899,0.005015344,0.001961483,0.0005591809,0.00019668,0.002173654,0.01669637,0.0007452033,0.1498827,0.04830974,0.7734421],"study_design_scores_gemma":[0.0007166252,0.00007990269,0.0003190952,0.0001198566,0.00001469804,0.00006868532,0.000619647,0.003393263,0.007927482,0.008744751,0.977344,0.0006519806],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.05456245,0.0003195409,0.00677656,0.00009454897,0.000568113,0.0002465905,0.0005386451,0.0007908747,0.9361027],"genre_scores_gemma":[0.9946539,0.00002588539,0.0002582505,0.0001495626,0.0002057839,0.00004341053,0.0008114591,0.00008466281,0.003767085],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9400914,"threshold_uncertainty_score":0.9999992,"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."}}