{"id":"W3154533874","doi":"10.3390/stats4020021","title":"A Flexible Multivariate Distribution for Correlated Count Data","year":2021,"lang":"en","type":"article","venue":"Stats","topic":"Statistical Methods and Bayesian Inference","field":"Mathematics","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Count data; Multivariate statistics; Negative binomial distribution; Poisson distribution; Statistics; Dispersion (optics); Mathematics; Multivariate analysis of variance; Multivariate normal distribution; Multivariate analysis; Overdispersion; Computer science; Physics","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":[0.0003574863,0.00009043491,0.0001751109,0.000009176882,0.00008530714,0.00004512461,0.0001543587,0.00005725155,0.0002277464],"category_scores_gemma":[0.004774261,0.00007975355,0.00002532059,0.0001241914,0.00003178175,0.00007540151,0.0001135471,0.00008691027,0.00002121719],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003362022,"about_ca_system_score_gemma":0.0001120699,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000196178,"about_ca_topic_score_gemma":0.00001087333,"domain_scores_codex":[0.9990981,0.0000743292,0.0002157563,0.0002752933,0.0001267927,0.0002097363],"domain_scores_gemma":[0.9976819,0.001497615,0.00006759084,0.0004985904,0.000190493,0.00006377377],"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":[0.00004555922,0.0001212035,0.0000457032,0.000111965,0.00003860617,0.0000194363,0.00008531531,3.701938e-7,0.0007478786,0.9253845,0.02570235,0.04769713],"study_design_scores_gemma":[0.0005927207,0.00003976984,0.0006191471,0.00006200808,0.00006325928,0.000007628441,0.00005793924,0.01870538,0.00213983,0.9616371,0.01593533,0.0001398632],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0004673462,0.00003684067,0.9919847,0.0001834389,0.0002781255,0.0001923312,0.006131663,0.00006802149,0.000657585],"genre_scores_gemma":[0.02042783,0.0000107049,0.9768691,0.00006685779,0.00006221495,0.00002499424,0.001947181,0.00001724372,0.0005738747],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.04755726,"threshold_uncertainty_score":0.5715581,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2343690777199644,"score_gpt":0.4616250624967598,"score_spread":0.2272559847767954,"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."}}