{"id":"W4323038373","doi":"10.2196/46876","title":"ChatGPT in Clinical Toxicology","year":2023,"lang":"en","type":"article","venue":"JMIR Medical Education","topic":"Artificial Intelligence in Healthcare and Education","field":"Medicine","cited_by":93,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Clinical toxicology; Toxicology; Medicine; Pharmacology; Medical emergency; Biology","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":[0.0188582,0.0007564476,0.000786261,0.002616329,0.001582704,0.003483055,0.001911898,0.004121063,0.08037851],"category_scores_gemma":[0.1565057,0.0006091717,0.0009281832,0.001944035,0.001693573,0.006048683,0.006809067,0.004325456,0.03812011],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001942353,"about_ca_system_score_gemma":0.005154767,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006407405,"about_ca_topic_score_gemma":0.01028452,"domain_scores_codex":[0.9760719,0.01427769,0.002363606,0.001673731,0.004426158,0.001186878],"domain_scores_gemma":[0.7788538,0.1680904,0.006640583,0.009393769,0.02223655,0.01478475],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00129068,0.0003726737,0.01143235,0.001385963,0.00005080637,0.001877256,0.001721098,0.0003998197,0.0009001985,0.002728335,0.7169906,0.2608502],"study_design_scores_gemma":[0.0006290821,0.001220424,0.02294762,0.002805927,0.0001119026,0.009325296,0.001815627,0.001846241,0.002720448,0.01151655,0.9448417,0.0002191775],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.06786595,0.06581987,0.04075823,0.3709031,0.02574079,0.002518425,0.0189107,0.04269078,0.3647921],"genre_scores_gemma":[0.469938,0.03738472,0.08267201,0.2436711,0.02749132,0.003778746,0.02093025,0.008458375,0.1056756],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.08037851,"threshold_uncertainty_score":0.2688929,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1871568930161824,"score_gpt":0.572339741098651,"score_spread":0.3851828480824687,"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."}}