{"id":"W4402626454","doi":"10.1016/j.aej.2024.08.008","title":"A novel statistical approach to COVID-19 variability using the Weibull-Inverse Nadarajah Haghighi distribution","year":2024,"lang":"en","type":"article","venue":"Alexandria Engineering Journal","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"King Saud University","keywords":"Weibull distribution; Coronavirus disease 2019 (COVID-19); Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); 2019-20 coronavirus outbreak; Inverse; Statistics; Distribution (mathematics); Econometrics; Mathematics; Environmental science; Computer science; Virology; Outbreak; Medicine; Mathematical analysis","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0064689,0.0009203732,0.001088396,0.003353112,0.0008232099,0.002536344,0.002550337,0.001305052,0.00210919],"category_scores_gemma":[0.01642969,0.0004895031,0.00155601,0.00327574,0.00184693,0.002925177,0.002179191,0.002552862,0.0006746996],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001660416,"about_ca_system_score_gemma":0.002011427,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004357131,"about_ca_topic_score_gemma":0.00350748,"domain_scores_codex":[0.9970591,0.0009819114,0.0001605281,0.0007170025,0.0008793423,0.000202076],"domain_scores_gemma":[0.9928681,0.004351044,0.0008088384,0.0007117873,0.001122335,0.0001380218],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001186364,0.0001038987,0.02199547,0.0002710753,0.0002546574,0.0006710335,0.0005102243,0.4458644,0.00359736,0.3087713,0.006473244,0.2113688],"study_design_scores_gemma":[0.00001076904,0.00007242857,0.004659284,0.00006117721,0.00004145308,0.000542564,0.0001395211,0.9090664,0.001046012,0.07611087,0.008174211,0.00007514821],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.004503491,0.0003033397,0.9936112,0.0001877085,0.00004639212,0.00003834176,0.00009461194,0.0001382039,0.001076754],"genre_scores_gemma":[0.5287396,0.00241721,0.457538,0.0004148973,0.0005047937,0.0005511098,0.001348504,0.000262573,0.008223209],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.0064689,"threshold_uncertainty_score":0.03421128,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0823225644295879,"score_gpt":0.3586147551737154,"score_spread":0.2762921907441275,"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."}}