{"id":"W4382192792","doi":"10.2196/47068","title":"The Role of Social Media for Identifying Adverse Drug Events Data in Pharmacovigilance: Protocol for a Scoping Review","year":2023,"lang":"en","type":"review","venue":"JMIR Research Protocols","topic":"Pharmacovigilance and Adverse Drug Reactions","field":"Pharmacology, Toxicology and Pharmaceutics","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"U.S. National Library of Medicine","keywords":"Pharmacovigilance; Social media; Medicine; Adverse effect; Protocol (science); Intervention (counseling); Adverse drug reaction; Public health; Medical emergency; Internet privacy; Intensive care medicine; Drug; Alternative medicine; Pharmacology; Psychiatry; Nursing; Computer science","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":[0.1139533,0.005028707,0.01223628,0.0209983,0.005195087,0.009163767,0.005623912,0.009571533,0.07567596],"category_scores_gemma":[0.1316324,0.005490124,0.01511493,0.01781327,0.00531526,0.008505744,0.007557963,0.006811208,0.01458225],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01580772,"about_ca_system_score_gemma":0.07937586,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006009782,"about_ca_topic_score_gemma":0.01130731,"domain_scores_codex":[0.9401802,0.02441631,0.02256583,0.003253107,0.006918881,0.002665551],"domain_scores_gemma":[0.8918639,0.03725151,0.02159938,0.008282151,0.03676594,0.004237125],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"systematic_review","study_design_gemma":"not_applicable","study_design_scores_codex":[0.006498526,0.0006096477,0.001101492,0.8433315,0.001384852,0.001151341,0.00433088,0.001538596,0.002765695,0.006040085,0.05528933,0.07595818],"study_design_scores_gemma":[0.0127037,0.002036272,0.005014004,0.6030757,0.003580362,0.0006469292,0.003252203,0.001163977,0.002408303,0.008575075,0.357042,0.0005014317],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"protocol","genre_gemma":"protocol","genre_scores_codex":[0.0002435065,0.00113135,0.0009510519,0.0003685294,0.0002207624,0.9940385,0.002387626,0.00005790576,0.0006007655],"genre_scores_gemma":[0.0002312127,0.0008681001,0.002692043,0.0001383885,0.00002489358,0.995356,0.0004094927,0.000006415957,0.0002735914],"genre_candidate":"protocol","genre_consensus":"protocol","teacher_disagreement_score":0.1139533,"threshold_uncertainty_score":0.6026498,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.8456474926792266,"score_gpt":0.762516312388987,"score_spread":0.08313118029023958,"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."}}