{"id":"W3195400065","doi":"10.3390/info12090344","title":"VERONICA: Visual Analytics for Identifying Feature Groups in Disease Classification","year":2021,"lang":"en","type":"article","venue":"Information","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Interpretability; Visual analytics; Computer science; Naive Bayes classifier; Random forest; Machine learning; Analytics; Predictive analytics; Support vector machine; Interactive visual analysis; Artificial intelligence; Visualization; Data mining; Decision tree; Data science","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":[0.004373094,0.001831888,0.000888794,0.005864148,0.0007429923,0.003846934,0.001765449,0.0009594822,0.01296807],"category_scores_gemma":[0.0171283,0.0005839429,0.001399369,0.002799605,0.0006336026,0.002861877,0.003819478,0.001762798,0.002778386],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000639305,"about_ca_system_score_gemma":0.001343579,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004469723,"about_ca_topic_score_gemma":0.005015712,"domain_scores_codex":[0.9984314,0.0005956684,0.0001596858,0.0002750425,0.0004414874,0.0000966451],"domain_scores_gemma":[0.9930571,0.004570836,0.0004649699,0.0007886221,0.0008021546,0.0003162858],"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":[0.001661311,0.0004125142,0.01174744,0.001481315,0.0003512792,0.0006626183,0.002747294,0.01745544,0.01527045,0.03255117,0.1499608,0.7656983],"study_design_scores_gemma":[0.0005426678,0.0004568681,0.01109318,0.0008207952,0.0002057588,0.0008847106,0.0008858601,0.6589392,0.02289646,0.1350937,0.1678182,0.0003626658],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01431261,0.0008019155,0.8623392,0.001430288,0.0002777512,0.0007251689,0.01107968,0.1038891,0.005144395],"genre_scores_gemma":[0.1063862,0.0006338308,0.8755533,0.0004854584,0.0001197349,0.001036253,0.009999326,0.00335104,0.002434834],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01296807,"threshold_uncertainty_score":0.04338247,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04556151753470707,"score_gpt":0.3394224635250304,"score_spread":0.2938609459903234,"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."}}