{"id":"W4220713636","doi":"10.1111/biom.13657","title":"Zero-Inflated Poisson Models with Measurement Error in the Response","year":2022,"lang":"en","type":"article","venue":"Biometrics","topic":"Statistical Methods and Bayesian Inference","field":"Mathematics","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University; University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Count data; Poisson distribution; Observational error; Computer science; Identifiability; Estimator; Inference; Statistics; Errors-in-variables models; Bayesian probability; Algorithm; Zero (linguistics); Zero-inflated model; Data mining; Mathematics; Poisson regression; Artificial intelligence; Population","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":[0.005383844,0.0001203801,0.0001820112,0.0007481435,0.0001534669,0.00004177623,0.000344792,0.00003556375,0.00009093848],"category_scores_gemma":[0.003180118,0.00007614086,0.00003186689,0.005235205,0.00004025641,0.00004300251,0.00008341854,0.000239603,0.000004195399],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002143301,"about_ca_system_score_gemma":0.0000966907,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003839092,"about_ca_topic_score_gemma":0.000005180038,"domain_scores_codex":[0.9972674,0.0008868334,0.0002653936,0.0002059435,0.001124406,0.0002500294],"domain_scores_gemma":[0.9973183,0.002069416,0.0001012272,0.0003496794,0.0001125732,0.0000488392],"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":[0.002912948,0.001475743,0.001055666,0.0001317831,0.00008875851,0.0003513881,0.004437689,0.0001468021,0.003139148,0.9164966,0.009020093,0.06074337],"study_design_scores_gemma":[0.001303957,0.00119832,0.008228163,0.00003650061,0.00006203299,0.00004616834,0.0009799671,0.01045444,0.0002770983,0.9723372,0.004695321,0.0003808659],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05986197,0.0001309083,0.9373392,0.0009289326,0.00009445401,0.000450281,0.00005719871,0.00004862067,0.001088449],"genre_scores_gemma":[0.740761,0.000002865155,0.258917,0.0001714609,0.000008682603,0.00007916302,0.000001651477,0.00001522608,0.00004296993],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.680899,"threshold_uncertainty_score":0.3807128,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2521107688962931,"score_gpt":0.3774920384207777,"score_spread":0.1253812695244845,"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."}}