{"id":"W3080655609","doi":"10.1016/j.cmpb.2020.105724","title":"White learning methodology: A case study of cancer-related disease factors analysis in real-time PACS environment","year":2020,"lang":"en","type":"article","venue":"Computer Methods and Programs in Biomedicine","topic":"AI in cancer detection","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"Lakehead University","funders":"Fundo para o Desenvolvimento das Ciências e da Tecnologia; Universidade de Macau","keywords":"Machine learning; Artificial intelligence; Deep learning; Black box; Computer science; White box; Bayesian network; Naive Bayes classifier; Support vector machine","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":[0.004231583,0.0004791085,0.0003783112,0.001487914,0.00105069,0.001689959,0.001378055,0.001497898,0.002846848],"category_scores_gemma":[0.008341685,0.0002307149,0.0006063071,0.001669561,0.0006579972,0.001002286,0.0009887321,0.0006538265,0.0006581208],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008064213,"about_ca_system_score_gemma":0.001782924,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004909509,"about_ca_topic_score_gemma":0.006378648,"domain_scores_codex":[0.9973922,0.001246942,0.0001553582,0.0004333355,0.0005763575,0.0001958509],"domain_scores_gemma":[0.9937649,0.00421157,0.000327053,0.0005154165,0.0008374745,0.0003436287],"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":[0.0009555671,0.002087532,0.1331207,0.0008907591,0.0003868041,0.01428608,0.01175807,0.06307355,0.02418588,0.0116572,0.009005794,0.7285921],"study_design_scores_gemma":[0.0002421936,0.001995101,0.1089433,0.0002490922,0.0004656421,0.01671479,0.01374172,0.6995342,0.0658289,0.02101243,0.07099164,0.0002811342],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5296164,0.0003790824,0.4577896,0.00148439,0.0000739588,0.0005530512,0.0005624453,0.001207906,0.0083333],"genre_scores_gemma":[0.791639,0.0002531696,0.2016232,0.0002174259,0.0000438254,0.0001670203,0.0003766601,0.0002217085,0.005457887],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004909509,"threshold_uncertainty_score":0.02237904,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1136190132876436,"score_gpt":0.3892890498358598,"score_spread":0.2756700365482163,"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."}}