{"id":"W2034224025","doi":"10.1016/j.insmatheco.2010.09.002","title":"Distributional analysis of a generalization of the Polya process","year":2010,"lang":"en","type":"article","venue":"Insurance Mathematics and Economics","topic":"Bayesian Methods and Mixture Models","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Mathematics; Infinite divisibility; Geometric distribution; Negative binomial distribution; Generalization; Poisson distribution; Compound Poisson distribution; Exponential distribution; Distribution (mathematics); Compound Poisson process; Applied mathematics; Mathematical analysis; Pure mathematics; Probability distribution; Poisson process; Statistics; Poisson regression","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0002053424,0.00005033403,0.0001687729,0.00004269247,0.00003408179,0.00001965611,0.000256343,0.0000347844,0.000003261673],"category_scores_gemma":[0.00002301357,0.00003574465,0.00006225269,0.0001915299,0.00005449713,0.00008247997,0.00004891626,0.00004357678,1.318143e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000003154193,"about_ca_system_score_gemma":0.00002619417,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004625202,"about_ca_topic_score_gemma":0.00001799942,"domain_scores_codex":[0.9995768,0.000007096694,0.0002209573,0.00009566099,0.0000408635,0.0000586246],"domain_scores_gemma":[0.9994184,0.00003735385,0.0002069223,0.0002626957,0.00005542476,0.00001918058],"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":[8.703868e-7,0.00004616931,0.01200713,0.00004703085,0.00008135426,3.003767e-8,0.0006147192,0.0005359745,0.001635878,0.9805071,0.000003928815,0.00451985],"study_design_scores_gemma":[0.0001095855,0.000007578761,0.04195911,0.000009947349,0.00005756876,0.00000330746,0.000008379727,0.721027,0.009284455,0.2274163,0.00003183361,0.00008488874],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5132619,0.00001099087,0.4864378,0.00006246166,0.00004557542,0.00002805518,0.00002373419,0.000002304036,0.0001271445],"genre_scores_gemma":[0.8483709,0.00001657407,0.1515717,0.00002018483,0.000008192739,0.000002375672,0.000001493245,0.000001901087,0.000006679233],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7530907,"threshold_uncertainty_score":0.1457624,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008771929261194198,"score_gpt":0.2385647301075869,"score_spread":0.2297928008463928,"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."}}