{"id":"W3012093691","doi":"10.1016/j.autrev.2020.102508","title":"Precision health: A pragmatic approach to understanding and addressing key factors in autoimmune diseases","year":2020,"lang":"en","type":"review","venue":"Autoimmunity Reviews","topic":"Immunodeficiency and Autoimmune Disorders","field":"Immunology and Microbiology","cited_by":31,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"European League Against Rheumatism; Agência Nacional de Águas","keywords":"Precision medicine; Context (archaeology); Data science; Computer science; Public health; Engineering ethics; Knowledge management; Artificial intelligence; Medicine; Engineering; Biology","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":["metaepi_narrow"],"category_scores_codex":[0.002019711,0.001321867,0.00670676,0.0007871485,0.0009708703,0.0001750806,0.001273329,0.0007074552,0.0001089465],"category_scores_gemma":[0.001248808,0.001036746,0.0008655431,0.001767396,0.0003794933,0.0003126743,0.0008995837,0.002284603,0.0004101345],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007662119,"about_ca_system_score_gemma":0.0006999593,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003630866,"about_ca_topic_score_gemma":0.000007556741,"domain_scores_codex":[0.9899817,0.004600058,0.002991115,0.001133061,0.0001445114,0.001149521],"domain_scores_gemma":[0.9962531,0.0008411847,0.001466214,0.001341942,0.00002668977,0.00007084231],"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":[0.00001827669,0.0004292821,0.000007674733,0.02261111,0.0001774655,0.000003071357,0.00486785,0.000002296777,0.000016517,0.0008902815,0.0004201882,0.970556],"study_design_scores_gemma":[0.0005689171,0.0001531853,0.0001955065,0.04036186,0.0003863736,0.0000577604,0.001061455,0.000008340066,4.654977e-7,0.0001311942,0.956155,0.0009199252],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00002214793,0.9921829,0.0006553507,0.0001615782,0.0005888478,0.005143483,0.0001429369,0.0002015459,0.0009012611],"genre_scores_gemma":[0.0007362781,0.9962278,0.0001583278,0.0002188021,0.000005993355,0.0004444424,0.001772507,0.0001284657,0.0003073934],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9696361,"threshold_uncertainty_score":0.9999533,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1650647700577434,"score_gpt":0.3594390363221101,"score_spread":0.1943742662643666,"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."}}