{"id":"W4210874944","doi":"10.2196/32543","title":"Artificial Intelligence–Enabled Social Media Analysis for Pharmacovigilance of COVID-19 Vaccinations in the United Kingdom: Observational Study","year":2022,"lang":"en","type":"article","venue":"JMIR Public Health and Surveillance","topic":"Pharmacovigilance and Adverse Drug Reactions","field":"Pharmacology, Toxicology and Pharmaceutics","cited_by":38,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"UK Research and Innovation; Government of the United Kingdom; Engineering and Physical Sciences Research Council; Scottish Government","keywords":"Pharmacovigilance; Observational study; Social media; Coronavirus disease 2019 (COVID-19); Vaccination; 2019-20 coronavirus outbreak; Environmental health; Medicine; Data science; Family medicine; Virology; Internet privacy; Computer science; Outbreak; World Wide Web; Pharmacology; Adverse effect","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":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.00587055,0.0001887169,0.0004648507,0.0007186106,0.001523306,0.00003500345,0.0004414293,0.00007256886,0.0004798553],"category_scores_gemma":[0.0006788343,0.0001731115,0.0001364145,0.003790874,0.00009909647,0.0001470813,0.0000888355,0.0007207652,0.000001701713],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002477795,"about_ca_system_score_gemma":0.001086208,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001883635,"about_ca_topic_score_gemma":0.0006391053,"domain_scores_codex":[0.9956848,0.00215906,0.0008026188,0.0003916133,0.0003805505,0.0005813542],"domain_scores_gemma":[0.9956921,0.003222851,0.0004140905,0.0001629958,0.0001599331,0.0003480057],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0008672628,0.003588513,0.904892,0.0001943918,0.0006554165,0.00001646328,0.03616475,0.01571842,0.0001324081,0.02229157,0.008912692,0.006566147],"study_design_scores_gemma":[0.002392235,0.0002846542,0.1555981,0.000001157994,0.00006352922,0.00001078678,0.02816839,0.04699139,0.00001077762,0.001866593,0.7641908,0.000421604],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9569035,0.0001450305,0.001180009,0.03829488,0.000465988,0.001866648,0.0009788983,0.00005879955,0.0001062331],"genre_scores_gemma":[0.9842649,0.00007916862,0.0000269855,0.01285431,0.0002015427,0.00165563,0.0008794814,0.00001199685,0.00002602986],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7552781,"threshold_uncertainty_score":0.9997766,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5443496671783672,"score_gpt":0.5426264483448469,"score_spread":0.001723218833520335,"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."}}