{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000404459,0.00008585484,0.0001010612,0.00008271945,0.0005111407,0.0001732287,0.0005784518,0.00001346476,0.000001830944],"category_scores_gemma":[0.0003730122,0.00008461687,0.00004035207,0.0004184892,0.00001979692,0.0005609534,0.0004675088,0.00009987334,0.000004721374],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006617825,"about_ca_system_score_gemma":0.0001936307,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004182861,"about_ca_topic_score_gemma":4.930782e-7,"domain_scores_codex":[0.9990113,0.00001005971,0.0004193267,0.0001018987,0.0002670253,0.0001903426],"domain_scores_gemma":[0.9988636,0.0003062111,0.0002174269,0.0004189713,0.00008979534,0.0001039362],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001275199,0.003234292,0.1768744,0.001025987,0.0004878418,0.00005033979,0.04871117,0.3071859,0.0002480218,0.08003455,0.09729218,0.2847278],"study_design_scores_gemma":[0.0002948125,0.0000462509,0.001456141,0.000005480306,0.00001418872,0.000001548015,0.0004451364,0.9753517,0.00001453268,0.0001463439,0.02211618,0.0001076648],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03389391,0.00001509956,0.9599735,0.0006335338,0.0003103741,0.0003612358,0.004300053,0.0002394115,0.0002728588],"genre_scores_gemma":[0.2478462,0.000002984084,0.7497827,0.001507818,0.0001177617,0.000157312,0.0003631166,0.00001937649,0.0002027138],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.6681658,"threshold_uncertainty_score":0.3931333,"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."}}