{"id":"W2432199245","doi":"10.2196/resprot.5621","title":"Using Social Media Data to Identify Potential Candidates for Drug Repurposing: A Feasibility Study","year":2016,"lang":"en","type":"article","venue":"JMIR Research Protocols","topic":"Pharmacovigilance and Adverse Drug Reactions","field":"Pharmacology, Toxicology and Pharmaceutics","cited_by":35,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"U.S. National Library of Medicine; National Institute of General Medical Sciences","keywords":"Repurposing; Drug repositioning; Social media; Drug; Drug development; Medicine; Data science; Computer science; Pharmacology; World Wide Web; Engineering","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":[0.01426176,0.0007260983,0.0005814509,0.004836395,0.0008285069,0.001479742,0.0008779174,0.00139112,0.001958656],"category_scores_gemma":[0.03632217,0.0004073985,0.000960751,0.001858363,0.0006340134,0.002721937,0.001439206,0.0006941354,0.0009803183],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005908208,"about_ca_system_score_gemma":0.001593436,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0045259,"about_ca_topic_score_gemma":0.006048812,"domain_scores_codex":[0.9880184,0.007919931,0.0009381255,0.0008458684,0.001769592,0.000508202],"domain_scores_gemma":[0.9141706,0.06517532,0.004659447,0.00329877,0.01035482,0.002341036],"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":[0.003620225,0.0130783,0.815468,0.002616549,0.0005101771,0.002107555,0.004467773,0.001589728,0.009411892,0.0004624731,0.002953432,0.1437139],"study_design_scores_gemma":[0.002329546,0.02554108,0.8332599,0.0007607616,0.00141104,0.003678002,0.02091918,0.0798683,0.01341253,0.001019935,0.01746635,0.0003332238],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"protocol","genre_scores_codex":[0.9879545,0.0001970283,0.003959931,0.000395562,0.00002803446,0.003996246,0.00211121,0.00009015281,0.00126733],"genre_scores_gemma":[0.9575506,0.0002967257,0.03308073,0.0002916822,0.00009207065,0.004004319,0.004002345,0.00002015398,0.0006612696],"genre_candidate":"protocol","genre_consensus":null,"teacher_disagreement_score":0.01426176,"threshold_uncertainty_score":0.07542431,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.8354165269847041,"score_gpt":0.7292692315110744,"score_spread":0.1061472954736298,"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."}}