{"id":"W4417101090","doi":"10.5539/ijsp.v12n5p1","title":"Marshall-Olkin Extended Generalized Exponential Distribution: Properties, Inference and Application to Traffic Data","year":2023,"lang":"","type":"article","venue":"International Journal of Statistics and Probability","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Estimator; Exponential distribution; Exponential function; Natural exponential family; Moment (physics); Exponential family; Statistical inference; Monte Carlo method; Inference; Exponentially modified Gaussian distribution","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001555528,0.0002972834,0.0004727499,0.0001481297,0.0002370633,0.0003938194,0.0007954183,0.000135008,0.0001977462],"category_scores_gemma":[0.0047577,0.000276056,0.00005298864,0.0003826054,0.0003742553,0.0003201769,0.0006051878,0.0003226023,0.00004276846],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001849228,"about_ca_system_score_gemma":0.0003233544,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003169164,"about_ca_topic_score_gemma":0.00003644648,"domain_scores_codex":[0.996402,0.0002081173,0.00156657,0.0005667891,0.0009507178,0.0003057701],"domain_scores_gemma":[0.9955637,0.0009111962,0.0007435076,0.0005302654,0.001822262,0.0004290463],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000592656,0.0008775031,0.0002954572,0.0004361479,0.0003564938,0.00003320519,0.0007004292,0.0007150931,0.0008175917,0.6982232,0.01490769,0.2820445],"study_design_scores_gemma":[0.002780383,0.0003871255,0.04483505,0.0004145975,0.0004241428,0.000184507,0.0002719792,0.5761085,0.000160122,0.3525473,0.02117437,0.0007119162],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08788247,0.0001717337,0.8825046,0.004943871,0.0004555534,0.0007797275,0.02320094,0.00003965827,0.00002149298],"genre_scores_gemma":[0.9436557,0.0007698265,0.05236164,0.0001188339,0.0002722638,0.0000565776,0.002670981,0.00002229657,0.00007184139],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8557733,"threshold_uncertainty_score":0.9999692,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09500284792028951,"score_gpt":0.3744694564293032,"score_spread":0.2794666085090137,"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."}}