{"id":"W3113829857","doi":"10.3390/ijerph18010268","title":"Artificial Intelligence Model of Drive-Through Vaccination Simulation","year":2020,"lang":"en","type":"article","venue":"International Journal of Environmental Research and Public Health","topic":"COVID-19 epidemiological studies","field":"Mathematics","cited_by":45,"is_retracted":false,"has_abstract":true,"ca_institutions":"Response Biomedical (Canada); York University","funders":"Public Health Agency; Public Health Agency of Canada","keywords":"Vaccination; Mass vaccination; Computer science; Key (lock); Artificial intelligence; Medicine; Virology; Computer security","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0006664441,0.0006827957,0.0008129741,0.0005944142,0.0004599918,0.001020765,0.001359556,0.001431499,0.004348441],"category_scores_gemma":[0.002604501,0.0004057803,0.0008114912,0.0006066695,0.0006127511,0.0007190066,0.0006008424,0.00119784,0.0004262997],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001107743,"about_ca_system_score_gemma":0.001036989,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03418262,"about_ca_topic_score_gemma":0.01029694,"domain_scores_codex":[0.9996542,0.00009880972,0.00002322212,0.0001031007,0.00005249351,0.00006818751],"domain_scores_gemma":[0.9984541,0.001042374,0.0001693631,0.00004394372,0.0002236937,0.0000665714],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001270219,0.00001151176,0.0008490646,0.00001043713,0.000008524901,0.00003339777,0.00001023552,0.9963186,0.00005923518,0.001407323,0.0001964673,0.001082451],"study_design_scores_gemma":[0.000002589654,0.000004604255,0.0001766522,0.000001531521,0.000002442994,0.000004266496,0.000002940206,0.9990972,0.00002303468,0.0005697933,0.0001129477,0.000001890316],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.500338,0.001444738,0.4497206,0.002750349,0.0003025702,0.0002563736,0.005596106,0.0009679376,0.03862333],"genre_scores_gemma":[0.9747334,0.0003748342,0.01383954,0.0001535525,0.00004712059,0.0002818642,0.001289498,0.00003698852,0.009243315],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03418262,"threshold_uncertainty_score":0.0679673,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.652044812693287,"score_gpt":0.5540424065355212,"score_spread":0.09800240615776579,"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."}}