{"id":"W2996331803","doi":"","title":"Towards continuous monitoring in personalized healthcare through digital twins","year":2019,"lang":"en","type":"article","venue":"Conference of the Centre for Advanced Studies on Collaborative Research","topic":"Digital Transformation in Industry","field":"Engineering","cited_by":58,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Health care; Computer science; Personalized medicine; Remote patient monitoring; Medicine; Bioinformatics; Biology; Political science; Nursing","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":[0.0002573053,0.0001867901,0.0003968608,0.00009695011,0.000108322,0.00007961325,0.0003594537,0.00007766152,0.0000100691],"category_scores_gemma":[0.0005613698,0.000143544,0.00006950879,0.0008957962,0.0002624772,0.0005569595,0.00008554369,0.0003955039,0.00001569169],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004011369,"about_ca_system_score_gemma":0.0002056183,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002768539,"about_ca_topic_score_gemma":0.00001519649,"domain_scores_codex":[0.9983208,0.00007499411,0.0003626511,0.0002287336,0.0005366938,0.0004760939],"domain_scores_gemma":[0.9974512,0.0004756568,0.00006136511,0.0002737094,0.001687204,0.00005080503],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","study_design_scores_codex":[0.003864452,0.0009911968,0.06456058,0.01092684,0.002031853,0.00001999292,0.2735022,0.1052701,0.01361571,0.3711366,0.007720892,0.1463596],"study_design_scores_gemma":[0.008513078,0.001202872,0.001922982,0.006534415,0.0000161888,0.000001607036,0.6901607,0.00153854,0.1800749,0.01758705,0.09141653,0.001031109],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9496558,0.002313132,0.0001440014,0.003664775,0.001751005,0.003665545,0.0009620016,0.0001090332,0.03773467],"genre_scores_gemma":[0.9977031,0.0005345715,0.0002143783,0.000007311593,0.00003410491,0.000139388,0.00000587568,0.00002465601,0.001336579],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4166585,"threshold_uncertainty_score":0.5853555,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1130325869885511,"score_gpt":0.3934903295000144,"score_spread":0.2804577425114633,"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."}}