{"id":"W3035320939","doi":"10.2196/16739","title":"Understanding Drug Repurposing From the Perspective of Biomedical Entities and Their Evolution: Bibliographic Research Using Aspirin","year":2020,"lang":"en","type":"article","venue":"JMIR Medical Informatics","topic":"Computational Drug Discovery Methods","field":"Computer Science","cited_by":28,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Indiana University Bloomington; China Scholarship Council; National Natural Science Foundation of China; National Research Foundation","keywords":"Repurposing; Computer science; Popularity; Drug repositioning; Bibliometrics; Drug; Medicine; Data science; Pharmacology; Data mining; Engineering; Psychology","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":["bibliometrics"],"consensus_categories":[],"category_scores_codex":[0.002051298,0.0003569092,0.000667722,0.03809318,0.0007581608,0.002668031,0.0004476767,0.0006934984,0.002273257],"category_scores_gemma":[0.01604197,0.0001580653,0.0008559019,0.07774506,0.00048734,0.003757295,0.0008270836,0.0003671912,0.0003817362],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001722676,"about_ca_system_score_gemma":0.001813517,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01119197,"about_ca_topic_score_gemma":0.01247281,"domain_scores_codex":[0.998102,0.0004750823,0.0003424604,0.0003196425,0.0006503366,0.000110503],"domain_scores_gemma":[0.9796191,0.01242577,0.0050058,0.0006175455,0.001950751,0.0003809518],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000203838,0.0001916034,0.6770195,0.00598844,0.0008677954,0.001238328,0.004645074,0.002740231,0.004863418,0.01142603,0.004484198,0.2863316],"study_design_scores_gemma":[0.00001918906,0.0001573546,0.9349503,0.0012741,0.0009615265,0.001001843,0.00472529,0.009940077,0.002497982,0.004966344,0.03943513,0.0000708989],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8769089,0.07735867,0.007473209,0.003759031,0.0001261106,0.0001876336,0.01297772,0.0001422535,0.02106643],"genre_scores_gemma":[0.9456668,0.03901644,0.008255484,0.0002161426,0.0002484469,0.00009907732,0.005175793,0.00002527401,0.001296397],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9619068,"threshold_uncertainty_score":0.02225363,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2130642415602399,"score_gpt":0.3971146702360709,"score_spread":0.184050428675831,"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."}}