{"id":"W2917604803","doi":"10.5539/ijsp.v8n2p146","title":"Extended Poisson Inverse Weibull Distribution: Theoretical and Computational Aspects","year":2019,"lang":"en","type":"article","venue":"International Journal of Statistics and Probability","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Weibull distribution; Poisson distribution; Mathematics; Extension (predicate logic); Flexibility (engineering); Inverse; Applied mathematics; Maximum likelihood; Distribution (mathematics); Statistics; Mathematical optimization; Statistical physics; Computer science; Mathematical analysis; Geometry","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004855059,0.0001129345,0.0002035164,0.0000405715,0.00005781753,0.00008692544,0.0001333897,0.00005258448,0.0006734229],"category_scores_gemma":[0.001300881,0.00009692906,0.00003731704,0.00006251384,0.000312169,0.0001085574,0.00006084682,0.000175465,0.00001307816],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008272952,"about_ca_system_score_gemma":0.00008507857,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000308311,"about_ca_topic_score_gemma":0.000002077409,"domain_scores_codex":[0.998679,0.00007163148,0.000522514,0.0001636123,0.00045188,0.0001113152],"domain_scores_gemma":[0.9974428,0.001123065,0.0002814578,0.00009183087,0.0009139095,0.0001469126],"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":[0.00007409164,0.0001571799,0.001225963,0.00003699634,0.00005146199,0.000007938435,0.00006243162,0.00002701722,0.00002099286,0.9924161,0.002208371,0.003711449],"study_design_scores_gemma":[0.0007111556,0.000101764,0.04012957,0.00003337344,0.00003183578,0.000133093,0.00003602606,0.01536094,0.00002351294,0.9422848,0.00105789,0.00009604775],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1607615,0.00002517699,0.833205,0.002882031,0.0002339381,0.0002127013,0.001924276,0.00001547138,0.0007399194],"genre_scores_gemma":[0.9089544,0.00002502569,0.09066984,0.0001220642,0.0000549953,0.000003584137,0.0001384224,0.000006256365,0.00002537752],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7481929,"threshold_uncertainty_score":0.7373509,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02141711444499998,"score_gpt":0.326797567831217,"score_spread":0.305380453386217,"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."}}