{"id":"W3017227766","doi":"10.2196/17353","title":"Detecting and Filtering Immune-Related Adverse Events Signal Based on Text Mining and Observational Health Data Sciences and Informatics Common Data Model: Framework Development Study","year":2020,"lang":"en","type":"article","venue":"JMIR Medical Informatics","topic":"Pharmacovigilance and Adverse Drug Reactions","field":"Pharmacology, Toxicology and Pharmaceutics","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Human Genome Research Institute; National Institutes of Health","keywords":"Observational study; Data science; Informatics; Data mining; Computer science; Health informatics; Health data; Medicine; Health care; Public health; Engineering; Internal medicine; Pathology","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":[0.01076227,0.001062249,0.0014474,0.007148513,0.0008994858,0.003292484,0.001870116,0.001296784,0.0008297343],"category_scores_gemma":[0.01815293,0.0004831377,0.003922376,0.004256448,0.00118109,0.00297077,0.002698005,0.00166588,0.0003610202],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002840898,"about_ca_system_score_gemma":0.006657973,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02345283,"about_ca_topic_score_gemma":0.02164501,"domain_scores_codex":[0.9911211,0.002891735,0.001245146,0.002313295,0.002000469,0.00042828],"domain_scores_gemma":[0.9855828,0.007825074,0.001734639,0.001470803,0.002838156,0.0005485175],"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":[0.0009000241,0.002022,0.1313198,0.002368329,0.00205376,0.001760255,0.001559816,0.265526,0.01080759,0.1287073,0.01165188,0.4413232],"study_design_scores_gemma":[0.00004072917,0.0001645605,0.006739404,0.0001006645,0.0001604433,0.000246917,0.0002047037,0.9720976,0.001688845,0.01462108,0.003899549,0.00003545807],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01853149,0.0004131547,0.9765162,0.0008485409,0.00003041536,0.0006943388,0.001285452,0.00112284,0.0005576007],"genre_scores_gemma":[0.2028341,0.0004926531,0.7904038,0.0003453942,0.00008082021,0.0009248315,0.004248306,0.00005073081,0.0006192963],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02345283,"threshold_uncertainty_score":0.05691701,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3511945429628822,"score_gpt":0.4961855859945183,"score_spread":0.1449910430316361,"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."}}