{"id":"W2922295508","doi":"10.1177/2054358119834283","title":"Identifying Mobile Applications Aimed at Self-Management in People With Chronic Kidney Disease","year":2019,"lang":"en","type":"article","venue":"Canadian Journal of Kidney Health and Disease","topic":"Mobile Health and mHealth Applications","field":"Health Professions","cited_by":33,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Medicine; Kidney disease; Self-management; Intensive care medicine; Disease; Internal medicine; Computer science; Artificial intelligence","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02104509,0.0007995813,0.003123136,0.01981802,0.001227132,0.003310596,0.001521038,0.002694159,0.004312214],"category_scores_gemma":[0.1059569,0.0006805368,0.003798378,0.01266366,0.001054017,0.005005216,0.003901572,0.001273594,0.0005799395],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002025658,"about_ca_system_score_gemma":0.01241617,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005354235,"about_ca_topic_score_gemma":0.01675356,"domain_scores_codex":[0.9776204,0.008911917,0.009160541,0.001030786,0.002758875,0.0005175262],"domain_scores_gemma":[0.8616505,0.1099762,0.01795744,0.001429047,0.008048533,0.000938297],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"systematic_review","study_design_gemma":"observational","study_design_scores_codex":[0.0005034237,0.0001114402,0.02857437,0.6936451,0.001699625,0.0007718987,0.006181912,0.0001237396,0.0004410472,0.001161765,0.006008767,0.260777],"study_design_scores_gemma":[0.0005141872,0.0008747921,0.05981452,0.845434,0.01130336,0.001765217,0.007613303,0.0002614511,0.0006615511,0.002100258,0.06953123,0.0001262006],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.06280102,0.9070266,0.00200697,0.005504888,0.0006211677,0.008062088,0.005521482,0.00006164736,0.008394158],"genre_scores_gemma":[0.2705532,0.6796711,0.02260035,0.005832837,0.0005153092,0.01575734,0.003830008,0.00004257148,0.001197244],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02104509,"threshold_uncertainty_score":0.1112984,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01323617078558189,"score_gpt":0.334286347317838,"score_spread":0.3210501765322561,"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."}}