{"id":"W4213036259","doi":"10.2196/32415","title":"Correction: Predicting Antituberculosis Drug–Induced Liver Injury Using an Interpretable Machine Learning Method: Model Development and Validation Study","year":2021,"lang":"en","type":"article","venue":"JMIR Medical Informatics","topic":"Drug-Induced Hepatotoxicity and Protection","field":"Pharmacology, Toxicology and Pharmaceutics","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Liver injury; Drug development; Drug; Artificial intelligence; Machine learning; Medicine; Medical physics; Pharmacology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005850984,0.001918491,0.002567697,0.003470712,0.00207024,0.003366346,0.003275919,0.007348146,0.05709717],"category_scores_gemma":[0.139851,0.001227027,0.001981491,0.002425804,0.0022217,0.001933931,0.00199585,0.009449827,0.02913124],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003098814,"about_ca_system_score_gemma":0.005941574,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01235076,"about_ca_topic_score_gemma":0.01244943,"domain_scores_codex":[0.9932006,0.001438119,0.001515645,0.000847993,0.002443485,0.0005541592],"domain_scores_gemma":[0.9025776,0.02174089,0.004200206,0.006743448,0.06165133,0.003086451],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001468403,0.00001561893,0.000291926,0.000452891,0.00005930864,0.0004057214,0.00005106278,0.0001145045,0.0001422221,0.0005067437,0.9890164,0.008796727],"study_design_scores_gemma":[0.0003631971,0.0001056334,0.004057986,0.001106978,0.000245784,0.002215797,0.0002645792,0.002511588,0.001910778,0.002755218,0.9843375,0.0001249529],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"editorial","genre_gemma":"methods","genre_scores_codex":[0.0006552297,0.0007839448,0.001908735,0.05400318,0.9377829,0.00007693448,0.002743414,0.0007102071,0.001335415],"genre_scores_gemma":[0.07371619,0.007562404,0.02354282,0.1729193,0.5191618,0.0008465203,0.006188576,0.003567316,0.1924951],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.05709717,"threshold_uncertainty_score":0.191009,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1349437411396076,"score_gpt":0.4463673666322791,"score_spread":0.3114236254926714,"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."}}