{"id":"W2507679269","doi":"10.1002/pds.4090","title":"Can social media data lead to earlier detection of drug‐related adverse events?","year":2016,"lang":"en","type":"article","venue":"Pharmacoepidemiology and Drug Safety","topic":"Pharmacovigilance and Adverse Drug Reactions","field":"Pharmacology, Toxicology and Pharmaceutics","cited_by":54,"is_retracted":false,"has_abstract":true,"ca_institutions":"Group for Research in Decision Analysis","funders":"","keywords":"Medicine; Adverse Event Reporting System; Social media; Sibutramine; Atorvastatin; Adverse effect; Internal medicine; World Wide Web; Weight loss; Computer science; Obesity","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004665282,0.00052599,0.0003699788,0.003010859,0.0002775294,0.001983125,0.0004428948,0.0009321754,0.005802939],"category_scores_gemma":[0.02718656,0.0002767143,0.00109817,0.002400342,0.0003147613,0.002006817,0.0008366174,0.0007950709,0.001296777],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004143072,"about_ca_system_score_gemma":0.0003680624,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003626312,"about_ca_topic_score_gemma":0.00607381,"domain_scores_codex":[0.9961284,0.001677412,0.0006271285,0.0007284491,0.0005713272,0.0002672304],"domain_scores_gemma":[0.963183,0.01461213,0.01793817,0.001266968,0.002274813,0.0007249856],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003789466,0.00008692827,0.9707082,0.0002399656,0.0003576524,0.00009702804,0.00016401,0.0001529482,0.0003801075,0.0001202716,0.001776879,0.02553711],"study_design_scores_gemma":[0.00004213899,0.000246536,0.98737,0.0002221815,0.000384627,0.0004177234,0.0004073316,0.003010279,0.001263946,0.0003860646,0.006220028,0.00002921218],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9645153,0.005751993,0.002648325,0.004663663,0.0007622939,0.0001828639,0.01357383,0.0001924595,0.007709152],"genre_scores_gemma":[0.9916478,0.001067564,0.001903713,0.0007241708,0.0006246878,0.00008302865,0.002509224,0.00002539854,0.001414373],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005802939,"threshold_uncertainty_score":0.02467269,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1251523078739059,"score_gpt":0.434621748955007,"score_spread":0.3094694410811011,"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."}}