{"id":"W6901747834","doi":"10.60692/kshef-yr185","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":"Greater South Information System","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Akaike information criterion; Bayesian information criterion; Exponent; Model selection; Residual; Moment (physics); Information Criteria; Selection (genetic algorithm); Bayesian probability","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":[0.002284436,0.0003483383,0.00038979,0.001460336,0.0007967447,0.001024807,0.001173685,0.0005701279,0.001618954],"category_scores_gemma":[0.007582402,0.0001552254,0.0006831823,0.001599257,0.0006285877,0.000912442,0.0008176596,0.0008345374,0.000127229],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002906927,"about_ca_system_score_gemma":0.002113239,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1632949,"about_ca_topic_score_gemma":0.09729574,"domain_scores_codex":[0.9993609,0.0002128205,0.00003072697,0.000163921,0.0001483218,0.00008338989],"domain_scores_gemma":[0.9980754,0.0009217263,0.0003053554,0.0002157393,0.0004174043,0.00006448705],"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":[0.0001853968,0.00006826117,0.1886731,0.0001698354,0.000184315,0.001243013,0.0009675327,0.4712801,0.001601518,0.1332316,0.009932402,0.1924629],"study_design_scores_gemma":[0.00001018572,0.00002543163,0.03201365,0.00002699142,0.00002710443,0.0003201554,0.0003747995,0.9464095,0.000551586,0.01522616,0.004973465,0.00004109542],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3837918,0.001509257,0.6043949,0.001271165,0.00005456883,0.0001669848,0.00204859,0.000544728,0.006217961],"genre_scores_gemma":[0.9368105,0.0009833983,0.057288,0.00006936018,0.00004110097,0.0001056368,0.001415437,0.0000622164,0.003224327],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8367051,"threshold_uncertainty_score":0.3246889,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0924717800640337,"score_gpt":0.3193788621329061,"score_spread":0.2269070820688724,"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."}}