{"id":"W4403714349","doi":"10.1016/j.jvacx.2024.100575","title":"COVID-19 vaccine evidence monitoring assisted by artificial Intelligence: An emergency system implemented by the Public Health Agency of Canada to capture and describe the trajectory of evolving pandemic vaccine literature","year":2024,"lang":"en","type":"article","venue":"Vaccine X","topic":"SARS-CoV-2 and COVID-19 Research","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Public Health Agency of Canada","funders":"Public Health Agency; Public Health Agency of Canada","keywords":"Pandemic; Agency (philosophy); Coronavirus disease 2019 (COVID-19); Virology; Public health; 2019-20 coronavirus outbreak; Trajectory; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Medicine; Medical emergency; Political science; Sociology; Nursing; Infectious disease (medical specialty); Pathology; Outbreak","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002505068,0.0003797957,0.0006554531,0.0003068798,0.0003533353,0.0001034983,0.0005932114,0.0001393494,0.0001082981],"category_scores_gemma":[0.00145323,0.0002284446,0.0001199041,0.00221833,0.00001785053,0.0002672625,0.0001668692,0.0007268526,0.000001330146],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009482655,"about_ca_system_score_gemma":0.003407508,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.09217893,"about_ca_topic_score_gemma":0.06210398,"domain_scores_codex":[0.9959834,0.000469068,0.001221837,0.0006708421,0.0008965185,0.000758302],"domain_scores_gemma":[0.9974356,0.0005524652,0.0002558046,0.0008173236,0.0005093793,0.0004294202],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001077939,0.0003383315,0.1835231,0.009966376,0.0007599449,0.0001237084,0.01813046,0.000008905756,0.4417117,0.0002423565,0.2755094,0.0686079],"study_design_scores_gemma":[0.006208437,0.009663642,0.189304,0.01882879,0.001765419,0.002750064,0.09059656,0.02776327,0.2303257,0.0003812619,0.4186563,0.003756531],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8635491,0.1151164,0.002060606,0.01624906,0.000835185,0.001749861,0.0002551415,0.0001381314,0.00004649395],"genre_scores_gemma":[0.9958719,0.0004362559,0.00004755403,0.003040275,0.0003400154,0.0001068987,0.0000333887,0.00005206673,0.00007162857],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2113859,"threshold_uncertainty_score":0.9550102,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1030261621416822,"score_gpt":0.3931811423212547,"score_spread":0.2901549801795724,"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."}}