{"id":"W4247585342","doi":"10.1002/9781118445112.stat06788.pub2","title":"Overdispersion","year":2016,"lang":"en","type":"other","venue":"Wiley StatsRef: Statistics Reference Online","topic":"Statistical Methods and Bayesian Inference","field":"Mathematics","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Overdispersion; Quasi-likelihood; Covariate; Statistics; Econometrics; Poisson distribution; Mathematics; Negative binomial distribution; Count data","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.08164184,0.001035137,0.002188014,0.005437666,0.001428858,0.0036207,0.003055427,0.00110235,0.01125679],"category_scores_gemma":[0.2228351,0.0006012357,0.001706371,0.00633419,0.004429255,0.003089165,0.004204499,0.002591323,0.002295755],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002262076,"about_ca_system_score_gemma":0.002130055,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001280312,"about_ca_topic_score_gemma":0.00223172,"domain_scores_codex":[0.8574985,0.06779369,0.01523037,0.02154679,0.03617322,0.001757491],"domain_scores_gemma":[0.6128195,0.2777028,0.03904081,0.05322665,0.01565904,0.001551181],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.001123323,0.0003540698,0.1134651,0.00622435,0.002699615,0.002931994,0.01289712,0.006837125,0.007908575,0.203461,0.07143558,0.5706621],"study_design_scores_gemma":[0.0001279771,0.0006534497,0.1079118,0.005286077,0.001614531,0.009178722,0.004860793,0.02081402,0.02432333,0.505505,0.3191791,0.0005451439],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1365576,0.0238519,0.7427018,0.008392029,0.005145991,0.002826983,0.011509,0.003215248,0.06579952],"genre_scores_gemma":[0.7883489,0.008368895,0.1578441,0.01336112,0.001556409,0.002942397,0.005206956,0.002061362,0.02030993],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.08164184,"threshold_uncertainty_score":0.4317685,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07573905880162594,"score_gpt":0.4099848360681055,"score_spread":0.3342457772664796,"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."}}