{"id":"W3041541684","doi":"10.29252/jirss.19.1.1","title":"Accurate Inference for the Mean of the Poisson-Exponential Distribution","year":2020,"lang":"en","type":"article","venue":"Journal of the Iranian Statistical Society","topic":"Bayesian Methods and Mixture Models","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"York University; Thompson Rivers University","funders":"","keywords":"Mathematics; Poisson distribution; Statistics; Exponential distribution; Inference; Exponential family; Poisson regression; Exponential function; Applied mathematics; Artificial intelligence; Computer science; Mathematical analysis; Demography","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008383295,0.0001028539,0.000203341,0.000002777208,0.0002710017,0.00009060127,0.001443165,0.00004704623,0.000009236782],"category_scores_gemma":[0.0006601343,0.00004337727,0.0004110002,0.0002222838,0.000173823,0.0001370647,0.0002501444,0.00036081,6.303061e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000351993,"about_ca_system_score_gemma":0.0001442195,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000865631,"about_ca_topic_score_gemma":0.000002090908,"domain_scores_codex":[0.9986517,0.0002159096,0.0004063006,0.0001235512,0.0004196629,0.0001828521],"domain_scores_gemma":[0.9980637,0.0009251546,0.0004336813,0.0002751527,0.0002066759,0.0000955841],"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":[0.0001673197,0.000155942,0.0003067382,0.0001415778,0.0003879459,0.000003615465,0.009960095,0.0004923589,0.007330541,0.8337461,0.06367593,0.08363184],"study_design_scores_gemma":[0.002441562,0.0004759562,0.04122413,0.0001667254,0.0004771,0.00006231783,0.0003518241,0.6547785,0.007421986,0.273894,0.01830495,0.0004009091],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001099596,0.00006727665,0.9736501,0.0243766,0.0004713253,0.000177342,0.0001356318,0.00000552231,0.00001658467],"genre_scores_gemma":[0.798783,0.00002017924,0.1996553,0.001308051,0.0002099349,0.000001748215,5.945931e-7,0.000005273888,0.00001585073],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7976834,"threshold_uncertainty_score":0.2681785,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03465199919821783,"score_gpt":0.302961106923703,"score_spread":0.2683091077254852,"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."}}