{"id":"W4395003194","doi":"10.3390/math12081254","title":"A Novel Computational Instrument Based on a Universal Mixture Density Network with a Gaussian Mixture Model as a Backbone for Predicting COVID-19 Variants’ Distributions","year":2024,"lang":"en","type":"article","venue":"Mathematics","topic":"COVID-19 diagnosis using AI","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"King Abdulaziz University","keywords":"Mixture model; Coronavirus disease 2019 (COVID-19); Gaussian; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); 2019-20 coronavirus outbreak; Computer science; Statistical physics; Artificial intelligence; Biology; Virology; Physics; Medicine; Chemistry; Computational chemistry","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":[],"consensus_categories":[],"category_scores_codex":[0.000364466,0.0002850521,0.0003845517,0.0001380588,0.0002963719,0.0001040278,0.0001098558,0.0001656405,0.00004140183],"category_scores_gemma":[0.0005834168,0.0002321815,0.0001459411,0.0005040371,0.00009300779,0.00006518276,0.0000485468,0.0003332346,0.00001273112],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007912195,"about_ca_system_score_gemma":0.001835274,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003465837,"about_ca_topic_score_gemma":0.00004440817,"domain_scores_codex":[0.99834,0.00002474047,0.0003192372,0.0004459954,0.0005061507,0.0003639045],"domain_scores_gemma":[0.9978418,0.001222174,0.0001168708,0.0003459087,0.0001420992,0.0003310827],"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":[0.0006478961,0.001856862,0.0004082233,0.004175584,0.0004828602,0.0002383579,0.003256316,0.8725138,0.0002510654,0.0758778,0.04007592,0.0002153002],"study_design_scores_gemma":[0.002485154,0.0004133846,0.0001708472,0.001956234,0.0005616036,0.0001815957,0.0001425034,0.9819528,0.00002971288,0.009222954,0.002656007,0.0002272409],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01857141,0.00002465913,0.9374825,0.04165617,0.0001030062,0.001182823,0.0005428737,0.0003090889,0.000127498],"genre_scores_gemma":[0.6129898,0.000001968094,0.374352,0.01152496,0.0002275863,0.0001167757,0.0005109677,0.00007086079,0.0002051069],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.5944184,"threshold_uncertainty_score":0.9468086,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03240184684471877,"score_gpt":0.3005463070528993,"score_spread":0.2681444602081806,"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."}}