{"id":"W4200410514","doi":"10.1002/cjs.11678","title":"A model‐averaging treatment of multiple instruments in Poisson models with errors","year":2021,"lang":"en","type":"article","venue":"Canadian Journal of Statistics","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Instrumental variable; Covariate; Poisson regression; Poisson distribution; Variable (mathematics); Computer science; Econometrics; Regression analysis; Generalized linear model; Errors-in-variables models; Regression; Variables; Statistics; Mathematics; Machine learning","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"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":[0.01525232,0.001171788,0.001750025,0.001318898,0.0009418129,0.001379011,0.003167567,0.001823012,0.002918666],"category_scores_gemma":[0.05293002,0.00076595,0.002333594,0.002117658,0.001570939,0.002766283,0.002701593,0.003118035,0.0005553344],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009625693,"about_ca_system_score_gemma":0.002291644,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00285266,"about_ca_topic_score_gemma":0.002704811,"domain_scores_codex":[0.9927214,0.004706104,0.0002669067,0.0009527183,0.001027384,0.0003254489],"domain_scores_gemma":[0.9793032,0.01514514,0.001789213,0.002385742,0.001084847,0.0002918494],"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":[0.00009842555,0.0001846706,0.006227522,0.0002594788,0.0003802491,0.0003604238,0.0004417859,0.250972,0.00185794,0.5735039,0.004520694,0.1611929],"study_design_scores_gemma":[0.00002760192,0.0001027923,0.0006293534,0.00004541972,0.00008964754,0.00009021178,0.00003549887,0.7741646,0.001071145,0.2202905,0.00340681,0.00004645577],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002860799,0.0001460233,0.9961319,0.000243654,0.00005118095,0.00001978253,0.00002688477,0.00006794933,0.0004518646],"genre_scores_gemma":[0.2339117,0.001143411,0.7581241,0.0005719703,0.0007927945,0.000554554,0.0003180326,0.0002265616,0.004356779],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01525232,"threshold_uncertainty_score":0.08066297,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1555125557732044,"score_gpt":0.3231334217866085,"score_spread":0.1676208660134042,"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."}}