{"id":"W3011668859","doi":"10.1080/19466315.2020.1736142","title":"Clinical Trial Drug Safety Assessment With Interactive Visual Analytics","year":2020,"lang":"en","type":"article","venue":"Statistics in Biopharmaceutical Research","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Eli Lilly (Canada)","funders":"","keywords":"Visual analytics; Leverage (statistics); Analytics; Computer science; Patient safety; Drug reaction; Clinical trial; Data science; Medicine; Visualization; Data mining; Artificial intelligence; Health care; Drug","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":[0.05187776,0.003182692,0.001722399,0.01012384,0.0008349864,0.01034625,0.003783444,0.002698579,0.08431948],"category_scores_gemma":[0.2037282,0.00162687,0.003317803,0.00406022,0.0008511178,0.006135826,0.006921649,0.003434575,0.0186893],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002058691,"about_ca_system_score_gemma":0.004901402,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002270153,"about_ca_topic_score_gemma":0.003687981,"domain_scores_codex":[0.9689559,0.02039692,0.003916119,0.001329096,0.004824607,0.0005774125],"domain_scores_gemma":[0.7286906,0.2208434,0.008202002,0.01507308,0.02435717,0.002833717],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002786038,0.0003434176,0.003669114,0.00595646,0.0005873234,0.0005441172,0.002844739,0.008392804,0.002996946,0.01439349,0.365414,0.5920716],"study_design_scores_gemma":[0.00329986,0.000964126,0.007627929,0.008130827,0.0007791154,0.001408173,0.001471528,0.1340111,0.01507215,0.1028449,0.7234567,0.0009334733],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.009209935,0.005133512,0.7205759,0.02328866,0.002265585,0.00659963,0.028632,0.157557,0.04673785],"genre_scores_gemma":[0.07590942,0.003167247,0.877429,0.00455319,0.001743124,0.007592815,0.007327467,0.01211017,0.0101676],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.08431948,"threshold_uncertainty_score":0.2820767,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2941365035090849,"score_gpt":0.6015167684857263,"score_spread":0.3073802649766414,"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."}}