{"id":"W4394912493","doi":"10.1038/s41598-024-59720-1","title":"A novel flexible exponent power-X family of distributions with applications to COVID-19 mortality rate in Mexico and Canada","year":2024,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"King Khalid University","keywords":"Akaike information criterion; Bayesian information criterion; Weibull distribution; Exponent; Statistics; Mathematics; Residual; Model selection; Applied mathematics; Moment (physics); Selection (genetic algorithm); Function (biology); Bayesian probability; Computer science; Algorithm; Artificial intelligence; Physics","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":[0.0008097863,0.0001104278,0.0001698701,0.0001086829,0.0001877043,0.0001190019,0.0000813467,0.00002994978,0.00007400638],"category_scores_gemma":[0.0006385503,0.00009579585,0.00002424308,0.0009718413,0.0002022632,0.00006506781,0.00004591524,0.00007795081,0.000004025805],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002520296,"about_ca_system_score_gemma":0.001331195,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.02394749,"about_ca_topic_score_gemma":0.0672178,"domain_scores_codex":[0.9983945,0.0000245673,0.0005336642,0.0005025689,0.0003557143,0.0001889297],"domain_scores_gemma":[0.9986355,0.0002774493,0.0001145456,0.0005155557,0.0001524935,0.0003044137],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000004862794,0.0002446744,0.002451681,0.0002381425,0.00002887439,0.00005669264,0.0002394452,0.000282938,0.009557274,0.9475384,0.03916328,0.0001936774],"study_design_scores_gemma":[0.0005556053,0.00006264929,0.1376316,0.0003039928,0.0001707882,0.0001997637,0.0013499,0.004394645,0.01069908,0.5928755,0.250925,0.0008315241],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1108226,0.0000340512,0.8853369,0.001288635,0.0001911186,0.0007553027,0.0009791752,0.00007426363,0.0005179244],"genre_scores_gemma":[0.9929211,7.290012e-7,0.005843075,0.00009136836,0.000005277645,0.0004457787,0.0002981072,0.000008646878,0.0003858756],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8820986,"threshold_uncertainty_score":0.9825521,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07488560936088871,"score_gpt":0.3712111996927284,"score_spread":0.2963255903318396,"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."}}