{"id":"W3157493933","doi":"10.2196/27806","title":"A COVID-19 Pandemic Artificial Intelligence–Based System With Deep Learning Forecasting and Automatic Statistical Data Acquisition: Development and Implementation Study","year":2021,"lang":"en","type":"article","venue":"Journal of Medical Internet Research","topic":"COVID-19 epidemiological studies","field":"Mathematics","cited_by":57,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Ministry of Education, India","keywords":"Autoregressive integrated moving average; Artificial intelligence; Artificial neural network; Computer science; Pandemic; Feedforward neural network; Time series; Data set; Deep learning; Multilayer perceptron; Machine learning; Perceptron; Coronavirus disease 2019 (COVID-19); Data mining; Medicine","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.02072408,0.0001459047,0.0005153816,0.0001655791,0.0002508833,0.0001467429,0.0004011201,0.00009551155,0.0006296569],"category_scores_gemma":[0.04085516,0.00009530439,0.00002150287,0.0002587138,0.0002897009,0.0001037503,0.0008912527,0.001008005,0.000002578864],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004904577,"about_ca_system_score_gemma":0.001094565,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000131138,"about_ca_topic_score_gemma":0.001378257,"domain_scores_codex":[0.9940379,0.001911706,0.00116363,0.0003789659,0.002131741,0.0003760549],"domain_scores_gemma":[0.9829541,0.01548067,0.000313616,0.0001897096,0.0004144722,0.0006473691],"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":[0.0007794832,0.001161721,0.2530532,0.004277991,0.001084885,0.008767055,0.01722936,0.00009007969,0.00002343448,0.0154451,0.002044909,0.6960428],"study_design_scores_gemma":[0.002797734,0.003998531,0.01555656,0.002330357,0.0002664591,0.00312495,0.1755783,0.7809851,0.00009212773,0.01306335,0.001724273,0.0004821647],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5693542,0.0002575493,0.428263,0.00179616,0.00003464624,0.0002572237,0.00000335891,0.00002254168,0.00001128026],"genre_scores_gemma":[0.9778941,0.00003304812,0.0217269,0.0001679412,0.0001244033,0.00002055347,0.00001233435,0.00001208043,0.000008608747],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7808951,"threshold_uncertainty_score":0.9672241,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.6465545109775696,"score_gpt":0.5832018483240954,"score_spread":0.06335266265347417,"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."}}