{"id":"W3200683212","doi":"10.3390/e23091206","title":"Generalized Poisson Hurdle Model for Count Data and Its Application in Ear Disease","year":2021,"lang":"en","type":"article","venue":"Entropy","topic":"Bayesian Methods and Mixture Models","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Centre de Recherches Mathématiques","keywords":"Count data; Poisson distribution; Generalized linear model; Estimator; Quasi-likelihood; Zero-inflated model; Poisson regression; Statistics; Mathematics; Variance (accounting); Applied mathematics; Generalized estimating equation; Zero (linguistics); Overdispersion; Medicine; Population","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01040145,0.0007838215,0.001989486,0.002996062,0.0008420467,0.001946076,0.002809191,0.001968739,0.002614764],"category_scores_gemma":[0.03745025,0.0007782361,0.002307088,0.003555584,0.00202177,0.002685462,0.002564372,0.002752128,0.0007057287],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001456142,"about_ca_system_score_gemma":0.00164549,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007942001,"about_ca_topic_score_gemma":0.005076796,"domain_scores_codex":[0.9931754,0.004469773,0.0002667977,0.0008385245,0.0009917418,0.0002578954],"domain_scores_gemma":[0.9811368,0.01525152,0.001271286,0.001135888,0.0009364352,0.0002681778],"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":[0.00009994103,0.00005476938,0.01050493,0.0003788571,0.0002912857,0.0009625953,0.001011222,0.2331686,0.001035531,0.6656589,0.004833833,0.0819995],"study_design_scores_gemma":[0.00001773074,0.00005861932,0.002579283,0.00008740553,0.00006320357,0.0004369951,0.0001377174,0.6849113,0.0002540544,0.3055675,0.005814489,0.00007176554],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01379039,0.002119978,0.980974,0.0008126201,0.0001029765,0.00006145478,0.0001964036,0.0001689128,0.001773239],"genre_scores_gemma":[0.5267683,0.00834513,0.4502042,0.0007788311,0.0009366008,0.0007771669,0.001424865,0.0002746322,0.01049031],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01040145,"threshold_uncertainty_score":0.05500883,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04213906726764632,"score_gpt":0.3148376654365138,"score_spread":0.2726985981688674,"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."}}