{"id":"W2402735257","doi":"10.2139/ssrn.2618265","title":"Multivariate Pascal Mixture Regression Models for Correlated Claim Frequencies","year":2015,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Bayesian Methods and Mixture Models","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Multivariate statistics; Statistics; Econometrics; Mathematics; Multivariate analysis; Regression; Bayesian multivariate linear regression; Regression analysis; Multivariate adaptive regression splines","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02739313,0.002438284,0.004536442,0.006134835,0.002017867,0.006362967,0.01078114,0.006326262,0.01315838],"category_scores_gemma":[0.0952304,0.003537153,0.005451004,0.006095267,0.003998069,0.01038145,0.004162722,0.008708252,0.004535212],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002905813,"about_ca_system_score_gemma":0.002066482,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01511391,"about_ca_topic_score_gemma":0.01496593,"domain_scores_codex":[0.9859771,0.00888647,0.000517522,0.002194137,0.001556624,0.000868208],"domain_scores_gemma":[0.913075,0.07230577,0.004073741,0.006198907,0.003622704,0.0007238507],"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":[0.0003295219,0.0002266256,0.005034439,0.0002664237,0.0004333318,0.000262095,0.000716913,0.3347994,0.0006271579,0.5902107,0.007112289,0.05998113],"study_design_scores_gemma":[0.00002568582,0.00001780877,0.000973616,0.00004309136,0.00006645375,0.00009105927,0.00004501459,0.8786047,0.0001461395,0.1183272,0.001607592,0.00005171644],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01639611,0.0007170148,0.9789593,0.0009062357,0.00009416138,0.00009538924,0.0004877359,0.0004488916,0.001895231],"genre_scores_gemma":[0.4988341,0.003666646,0.440513,0.0007927681,0.001312164,0.001315669,0.004569328,0.001470076,0.04752621],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02739313,"threshold_uncertainty_score":0.1448705,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02948120052113161,"score_gpt":0.2881969412505078,"score_spread":0.2587157407293762,"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."}}