{"id":"W4210867473","doi":"10.1002/qre.3078","title":"Analyzing count data with measurement error","year":2022,"lang":"en","type":"article","venue":"Quality and Reliability Engineering International","topic":"Advanced Statistical Process Monitoring","field":"Decision Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Statistics; Observational error; Inference; Log-normal distribution; Count data; Statistical inference; Regression analysis; Mathematics; Population; Regression; Econometrics; Computer science; Artificial intelligence","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":[0.02092663,0.000879636,0.001162378,0.001857119,0.0005741228,0.001757354,0.002215925,0.001821001,0.0008246602],"category_scores_gemma":[0.1051644,0.0006915883,0.0009707591,0.002177418,0.002368321,0.002901238,0.001702949,0.002355793,0.0002057503],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001183325,"about_ca_system_score_gemma":0.001018443,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004353562,"about_ca_topic_score_gemma":0.002164802,"domain_scores_codex":[0.9859267,0.007738888,0.0007219301,0.002423168,0.002739236,0.0004500908],"domain_scores_gemma":[0.8546894,0.1176552,0.01211512,0.009813159,0.005203905,0.0005232844],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0002803405,0.0002596366,0.1349892,0.0003282535,0.000682795,0.0006282735,0.0004839601,0.725894,0.002820291,0.0566569,0.001138773,0.07583749],"study_design_scores_gemma":[0.00001863099,0.00006633059,0.009678807,0.00003422517,0.00004368309,0.000106073,0.00006947834,0.9597957,0.001382987,0.02819566,0.0005761674,0.00003214422],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1178659,0.0002750584,0.8803023,0.0004358189,0.00006424502,0.00006244676,0.0002068664,0.0002191209,0.0005682826],"genre_scores_gemma":[0.9180263,0.0002029265,0.07983518,0.0001537918,0.0001509873,0.0001451781,0.0005189247,0.00004831014,0.0009182464],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02092663,"threshold_uncertainty_score":0.1106719,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2238217057577922,"score_gpt":0.4341605126323592,"score_spread":0.2103388068745669,"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."}}