{"id":"W2971965618","doi":"10.23977/acss.2019.31005","title":"Application of Modern Computer Technology in Adverse Drug Reactions","year":2019,"lang":"en","type":"article","venue":"Advances in Computer Signals and Systems","topic":"Pharmacovigilance and Adverse Drug Reactions","field":"Pharmacology, Toxicology and Pharmaceutics","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Adverse drug reaction; Field (mathematics); Drug reaction; Data mining; Medical record; Computer science; Data science; Drug; Medicine; Pharmacology; Internal medicine","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":[0.001743539,0.0005765271,0.0005669481,0.004548261,0.000318285,0.001714384,0.00071766,0.0009479278,0.003861461],"category_scores_gemma":[0.004468919,0.0001917259,0.0007869164,0.003388294,0.0006391896,0.00168824,0.000801569,0.001152483,0.001163962],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009107873,"about_ca_system_score_gemma":0.001235189,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001647789,"about_ca_topic_score_gemma":0.001214699,"domain_scores_codex":[0.9982848,0.0005225312,0.0002257072,0.0002240495,0.0006728503,0.00006998688],"domain_scores_gemma":[0.9971644,0.001535635,0.0003340501,0.0002022103,0.0006912235,0.00007239423],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001364461,0.0001406257,0.01867561,0.004272656,0.0001940965,0.001011508,0.0004174136,0.002820355,0.005537824,0.02974038,0.01755474,0.9194983],"study_design_scores_gemma":[0.0001219725,0.0009180156,0.05860307,0.004364066,0.0006232818,0.01231698,0.001030864,0.02178321,0.01797427,0.1024908,0.779538,0.0002354308],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.03304704,0.7527613,0.1211973,0.01521523,0.003266546,0.0004294337,0.0009871122,0.000897604,0.07219844],"genre_scores_gemma":[0.2907449,0.575869,0.1074173,0.005777704,0.004946678,0.0003632422,0.00105698,0.00007669685,0.01374752],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004548261,"threshold_uncertainty_score":0.01291788,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03437384594873865,"score_gpt":0.3825548973349764,"score_spread":0.3481810513862378,"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."}}