{"id":"W4385304090","doi":"10.9734/jpri/2023/v35i207403","title":"COVID-19 Post Vaccination Data in North America","year":2023,"lang":"en","type":"article","venue":"Journal of Pharmaceutical Research International","topic":"Vaccine Coverage and Hesitancy","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"International Civil Aviation Organization","funders":"","keywords":"Public health; Pandemic; Vaccination; Milestone; Government (linguistics); Political science; Coronavirus disease 2019 (COVID-19); Public relations; Death toll; Medicine; Economic growth; Environmental health; Virology; Geography; Disease; Infectious disease (medical specialty); Nursing","routes":{"ca_aff":true,"ca_fund":false,"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":["metaresearch","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0059141,0.00006163192,0.0001268711,0.0009098027,0.0002306196,0.0001393338,0.001506763,0.0000484294,0.004385047],"category_scores_gemma":[0.02436173,0.00005669811,0.00005353266,0.001396239,0.00004806276,0.0008507132,0.0003579204,0.00072131,0.0002617976],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006837925,"about_ca_system_score_gemma":0.001888388,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003446422,"about_ca_topic_score_gemma":0.001897867,"domain_scores_codex":[0.9963498,0.0005787677,0.0004107451,0.0001789115,0.002073565,0.0004082681],"domain_scores_gemma":[0.9966792,0.001487237,0.0001148864,0.0001576792,0.0009549521,0.0006060459],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001184545,0.0007918283,0.3427867,0.00006646392,0.0002012228,0.002578098,0.01132113,0.0006031707,0.0008876428,0.01753168,0.4436825,0.178365],"study_design_scores_gemma":[0.001005318,0.00007270322,0.07407363,0.00001648133,0.000005692678,0.00001076425,0.002104017,0.003493486,0.00001859003,0.001654018,0.9174672,0.00007808417],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5917704,0.0005003912,0.0009739263,0.3818183,0.002041721,0.0004371369,0.0001835373,0.00006210561,0.02221259],"genre_scores_gemma":[0.993726,0.002489728,0.0001255606,0.001483159,0.001209058,0.000003556282,0.00006094788,0.000008438765,0.0008935482],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4737848,"threshold_uncertainty_score":0.9965251,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3677571065739081,"score_gpt":0.5913458236422656,"score_spread":0.2235887170683575,"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."}}