{"id":"W3120045999","doi":"10.1007/s10614-020-10082-6","title":"Finite Sample Lag Adjusted Critical Values of the ADF-GLS Test","year":2021,"lang":"en","type":"article","venue":"Computational Economics","topic":"Monetary Policy and Economic Impact","field":"Economics, Econometrics and Finance","cited_by":8,"is_retracted":false,"has_abstract":false,"ca_institutions":"Queen's University","funders":"","keywords":"Akaike information criterion; Mathematics; Lag; Sample (material); Econometrics; Inference; Statistics; Applied mathematics; Computer science","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002682432,0.0001527086,0.000397766,0.00008881844,0.0001424359,0.00006670671,0.0002750442,0.00009481498,0.001083673],"category_scores_gemma":[0.001975549,0.000170155,0.0002228322,0.0001179879,0.0001674499,0.0002276148,0.0001285022,0.0001401122,0.0003547546],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009783104,"about_ca_system_score_gemma":0.0000962643,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001162091,"about_ca_topic_score_gemma":0.00002686942,"domain_scores_codex":[0.9985285,0.00002348151,0.0008083618,0.0003556616,0.00002092048,0.0002630959],"domain_scores_gemma":[0.9967242,0.002478086,0.0003017372,0.0003595454,0.00004375339,0.00009270714],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000008052483,0.0001348933,0.07337417,0.00003675453,0.00006166391,0.00000118383,0.0002444883,0.6318734,0.000002788616,0.2926964,0.001178814,0.000387388],"study_design_scores_gemma":[0.0004362111,0.00003134123,0.07404191,0.00001419831,0.00001038563,0.00001113218,0.0000502527,0.5044765,0.0001219354,0.4109773,0.009604788,0.0002239965],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.944736,0.001239128,0.02709628,0.00726794,0.001604289,0.0002347021,0.005167313,0.00004669944,0.01260761],"genre_scores_gemma":[0.9920012,0.00007373627,0.005795994,0.001390559,0.0001908637,0.0000063072,0.0001183539,0.00002254441,0.0004004868],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1273969,"threshold_uncertainty_score":0.9998295,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09538382026477223,"score_gpt":0.2524697320356092,"score_spread":0.157085911770837,"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."}}