{"id":"W4387956984","doi":"10.3389/fphar.2023.1271309","title":"Big data- and machine learning-based analysis of a global pharmacovigilance database enables the discovery of sex-specific differences in the safety profile of dual IL4/IL13 blockade","year":2023,"lang":"en","type":"article","venue":"Frontiers in Pharmacology","topic":"Urticaria and Related Conditions","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Pharmacovigilance; Dupilumab; Medicine; Adverse effect; Interleukin 23; Database; Immunology; Pharmacology; Internal medicine; Interleukin 17; Immune system; Asthma","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":[0.0006238156,0.0001388276,0.0005823941,0.0003295845,0.00006059735,0.000005751795,0.0003406956,0.0000778655,0.00006581415],"category_scores_gemma":[0.00005710105,0.00008257299,0.00007513473,0.00213496,0.000597283,0.00007106953,0.0001482591,0.0003806695,5.793697e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003326446,"about_ca_system_score_gemma":0.0001370016,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001540348,"about_ca_topic_score_gemma":0.00006296635,"domain_scores_codex":[0.9982617,0.0004579461,0.0005024233,0.0003002036,0.0002362413,0.0002414853],"domain_scores_gemma":[0.9989579,0.0004274308,0.0002050661,0.0003369703,0.00003606045,0.00003659621],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001320952,0.000563912,0.9537563,0.0001201194,0.003231701,0.0001057335,0.001144777,0.002128628,0.0263813,0.00007284289,0.009072678,0.002101071],"study_design_scores_gemma":[0.01006871,0.0004589294,0.5246705,0.0001292586,0.0117668,0.0000208827,0.005914207,0.4253412,0.01421815,0.0001382599,0.006962507,0.0003104837],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9899208,0.002921302,0.001298502,0.001753279,0.0005003121,0.0004889091,0.002976063,0.00001611351,0.0001247476],"genre_scores_gemma":[0.9961817,0.002349931,0.0001424659,0.0001215372,0.00005730799,0.00003443817,0.001020469,0.000007162779,0.00008495956],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4290857,"threshold_uncertainty_score":0.3367229,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03743736397392785,"score_gpt":0.3015576692303584,"score_spread":0.2641203052564305,"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."}}