{"id":"W4207044924","doi":"10.1142/s0218348x22401466","title":"USE OF EVOLUTIONARY ALGORITHMS IN A FRACTIONAL FRAMEWORK TO PREVENT THE SPREAD OF CORONAVIRUS","year":2022,"lang":"en","type":"article","venue":"Fractals","topic":"COVID-19 epidemiological studies","field":"Mathematics","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"Fractional calculus; Mathematical optimization; Computer science; Coronavirus; Population; Outbreak; Order (exchange); Coronavirus disease 2019 (COVID-19); Optimal control; Mathematics; Disease; Applied mathematics; Economics; Medicine; Infectious disease (medical specialty)","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000826088,0.0001137631,0.0003909916,0.00006583051,0.0001125209,0.000003289953,0.0002473918,0.00005886219,0.0008528092],"category_scores_gemma":[0.007733379,0.00008242748,0.0001224699,0.0003406582,0.00008032832,0.0000621071,0.0005228507,0.000351054,0.000009612764],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002210757,"about_ca_system_score_gemma":0.00005517465,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006064906,"about_ca_topic_score_gemma":0.00002657254,"domain_scores_codex":[0.9982319,0.0003696654,0.0005570101,0.000207305,0.0004475715,0.0001864912],"domain_scores_gemma":[0.9873819,0.01190068,0.0002999163,0.0003196786,0.00006159196,0.00003621925],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001538478,0.01289753,0.454691,0.0006749713,0.001097025,0.0000889896,0.0109273,0.0597614,0.004329198,0.2202344,0.1819811,0.0517786],"study_design_scores_gemma":[0.0001940863,0.0003602747,0.4773089,0.0001176025,0.00004275287,0.000007981032,0.0004967914,0.0009840154,0.0002379212,0.4099634,0.1100658,0.0002205506],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9814049,0.0009103855,0.009786972,0.0058714,0.000300473,0.001044337,0.0003954696,0.00004240652,0.0002436714],"genre_scores_gemma":[0.975028,0.00003691908,0.0230906,0.001254832,0.00005847638,0.0002759156,0.000006889496,0.00001265302,0.0002356888],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1897289,"threshold_uncertainty_score":0.9337663,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3008548593624847,"score_gpt":0.4443358411412355,"score_spread":0.1434809817787507,"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."}}