{"id":"W3045129222","doi":"","title":"Visual Analytics of Electronic Health Records with a focus on Acute Kidney Injury","year":2020,"lang":"en","type":"article","venue":"Scholarship@Western (Western University)","topic":"Machine Learning in Healthcare","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Focus (optics); Visual analytics; Electronic health record; Health records; Acute kidney injury; Analytics; Medicine; Computer science; Visualization; Data science; Artificial intelligence; Political science; Internal medicine; Health care","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.002547356,0.0007733035,0.0003555164,0.005063497,0.0004341386,0.004040017,0.000656614,0.0006313244,0.004775932],"category_scores_gemma":[0.01427102,0.0002301786,0.0008362628,0.003604226,0.0006651648,0.002185478,0.002110999,0.0008292229,0.001031485],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007872514,"about_ca_system_score_gemma":0.001165739,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005720816,"about_ca_topic_score_gemma":0.005039357,"domain_scores_codex":[0.9984046,0.0007656781,0.0001327298,0.0002060299,0.0003943997,0.00009656576],"domain_scores_gemma":[0.9923458,0.00523508,0.0006511454,0.0004693537,0.001139381,0.0001591272],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001001581,0.0002568722,0.02128839,0.002820845,0.0002328934,0.000902006,0.0123433,0.02475864,0.01412137,0.06429092,0.06805822,0.789925],"study_design_scores_gemma":[0.0002639604,0.0005481568,0.07345516,0.003099753,0.0003525069,0.002018278,0.01646273,0.3333384,0.03021,0.1505688,0.389259,0.0004232246],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1729191,0.01170032,0.7076197,0.01667975,0.0008883164,0.001145938,0.01725355,0.01314398,0.05864941],"genre_scores_gemma":[0.5817109,0.006417311,0.3941022,0.001194404,0.0004574744,0.0004015546,0.007813909,0.0005796974,0.007322623],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005720816,"threshold_uncertainty_score":0.01597714,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05975822550037502,"score_gpt":0.343949177727872,"score_spread":0.284190952227497,"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."}}