{"id":"W4214540750","doi":"10.3390/informatics9010017","title":"Visual Analytics for Predicting Disease Outcomes Using Laboratory Test Results","year":2022,"lang":"en","type":"article","venue":"Informatics","topic":"Data Mining Algorithms and Applications","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Visual analytics; Computer science; Analytics; Sunrise; Visualization; Interactive visualization; Machine learning; Process (computing); Gradient boosting; Data mining; Artificial intelligence; Data science; Random forest","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.001780971,0.001703579,0.0005859868,0.00375808,0.0003469746,0.002177319,0.001272257,0.0006677099,0.008491279],"category_scores_gemma":[0.007939287,0.000427109,0.0007954639,0.001660111,0.000383444,0.0015457,0.001885851,0.000825083,0.001695575],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007722821,"about_ca_system_score_gemma":0.001012084,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01436291,"about_ca_topic_score_gemma":0.01817098,"domain_scores_codex":[0.9995098,0.0001363385,0.00004921652,0.00009278477,0.0001699482,0.00004190637],"domain_scores_gemma":[0.9957824,0.002812823,0.0002907396,0.0003329032,0.0005979396,0.0001833062],"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":[0.002498925,0.0004241264,0.03770522,0.002714138,0.0004294882,0.001432186,0.003943783,0.07432898,0.02167702,0.01889972,0.1243703,0.7115762],"study_design_scores_gemma":[0.0003456076,0.0003047038,0.02079025,0.0008363887,0.0002341647,0.0008236836,0.001202691,0.8008921,0.02208566,0.06006885,0.09217142,0.0002444709],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05580205,0.001583815,0.8004127,0.002323831,0.0002392231,0.0006681555,0.02528663,0.1017905,0.01189314],"genre_scores_gemma":[0.3802465,0.001472216,0.5992265,0.0005563321,0.0001422227,0.00056437,0.01259216,0.001777303,0.003422442],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01436291,"threshold_uncertainty_score":0.02855861,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02860503085346108,"score_gpt":0.3071740510001446,"score_spread":0.2785690201466835,"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."}}