{"id":"W4403487670","doi":"10.1097/hep.0000000000001074","title":"Boosting Success: Optimizing Thiopurine Therapy in Autoimmune Hepatitis With Allopurinol","year":2024,"lang":"en","type":"article","venue":"Hepatology","topic":"Liver Diseases and Immunity","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"London Health Sciences Centre; Western University","funders":"","keywords":"Thiopurine methyltransferase; Allopurinol; Boosting (machine learning); Medicine; Autoimmune hepatitis; Intensive care medicine; Hepatitis; Azathioprine; Internal medicine; Artificial intelligence; Computer science; Disease","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":[0.002721613,0.0004599068,0.000789966,0.0003157014,0.0004452604,0.001148783,0.0003446729,0.0003919127,0.001399416],"category_scores_gemma":[0.005816669,0.00008699539,0.0003655585,0.0002279631,0.0002719476,0.0008354111,0.0005646613,0.001182567,0.0003784663],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000544577,"about_ca_system_score_gemma":0.001198366,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006337605,"about_ca_topic_score_gemma":0.002055911,"domain_scores_codex":[0.9986382,0.0006089059,0.0001281436,0.00007095275,0.0003218498,0.0002319026],"domain_scores_gemma":[0.9979704,0.0006631237,0.0004819069,0.0001085586,0.0001905278,0.0005853723],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.007771705,0.00426014,0.06076876,0.0008125681,0.0006422599,0.0003720541,0.0005105066,0.00424764,0.009961228,0.002092064,0.006101727,0.9024593],"study_design_scores_gemma":[0.007442833,0.1102389,0.5895042,0.005791666,0.005056391,0.005167091,0.002424422,0.02892204,0.0509788,0.01876457,0.1754765,0.0002325427],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.911745,0.04582545,0.007124158,0.01426,0.0009667132,0.000369478,0.0001149262,0.0003740352,0.0192204],"genre_scores_gemma":[0.9854474,0.005414781,0.00595145,0.001106946,0.0007854681,0.00009453285,0.00004515942,0.00004268877,0.001111676],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002721613,"threshold_uncertainty_score":0.01439339,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01813330487900294,"score_gpt":0.2723063309330911,"score_spread":0.2541730260540881,"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."}}