{"id":"W4385281785","doi":"10.3389/fmed.2023.1233220","title":"Prediction of the occurrence of leprosy reactions based on Bayesian networks","year":2023,"lang":"en","type":"article","venue":"Frontiers in Medicine","topic":"Leprosy Research and Treatment","field":"Medicine","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University Health Centre","funders":"Conselho Nacional de Desenvolvimento Científico e Tecnológico; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior; Fundacion Araucaria","keywords":"Leprosy; Bayesian network; Bayesian probability; Computer science; Artificial intelligence; Machine learning; Medicine; Dermatology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004955812,0.00009259016,0.0003130482,0.000292909,0.00003967368,0.000001104075,0.00009943396,0.00006601398,0.00004403873],"category_scores_gemma":[0.0004421959,0.00005396343,0.00006163957,0.001088994,0.0002610151,0.00002346326,0.00001941858,0.0002593933,0.000001829869],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009280497,"about_ca_system_score_gemma":0.0001095395,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008830928,"about_ca_topic_score_gemma":0.000006066821,"domain_scores_codex":[0.9987536,0.00006844156,0.0003082043,0.0001819053,0.0004816531,0.0002061654],"domain_scores_gemma":[0.9992292,0.00009044101,0.0000946463,0.0004287999,0.0000713344,0.00008560663],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004954252,0.0002777328,0.8913581,0.0002072517,0.00006949138,0.00002497294,0.0002225345,0.002007635,0.0005352102,0.00004677138,0.09494326,0.009811627],"study_design_scores_gemma":[0.00577043,0.001948898,0.7649623,0.001993316,0.000137531,0.000006242723,0.0005878211,0.2185728,0.001970008,0.0003262708,0.003651531,0.00007285711],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7358677,0.00404459,0.1256127,0.06521832,0.01666974,0.01057563,0.0006837641,0.0006140135,0.04071346],"genre_scores_gemma":[0.9986887,0.0001744405,0.0003518628,0.00009906786,0.0001087955,0.00004344444,0.00008412098,0.000007917518,0.000441656],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2628209,"threshold_uncertainty_score":0.2200565,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03132896229410381,"score_gpt":0.298865920678435,"score_spread":0.2675369583843312,"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."}}