{"id":"W3005811290","doi":"10.1111/ajps.12506","title":"Beyond the Unit Root Question: Uncertainty and Inference","year":2020,"lang":"en","type":"article","venue":"American Journal of Political Science","topic":"Monetary Policy and Economic Impact","field":"Economics, Econometrics and Finance","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Inference; Extant taxon; Unit root; Computer science; Root (linguistics); Set (abstract data type); Relevance (law); Value (mathematics); Econometrics; Root cause; Data mining; Mathematics; Machine learning; Artificial intelligence; Engineering; Reliability engineering","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":[],"consensus_categories":[],"category_scores_codex":[0.001050368,0.0000879381,0.0002791725,0.00008259173,0.0001552409,0.0001108433,0.0004448827,0.00001564327,0.0001261705],"category_scores_gemma":[0.001000867,0.00006522887,0.00005304065,0.0003743929,0.001874969,0.0003696522,0.00007444975,0.0002149924,0.00006397699],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006570086,"about_ca_system_score_gemma":0.00008759448,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000952121,"about_ca_topic_score_gemma":0.000009386431,"domain_scores_codex":[0.9988123,0.00002678394,0.0004515622,0.0001762155,0.00006225285,0.0004708634],"domain_scores_gemma":[0.9986723,0.0001899429,0.000333703,0.0001280472,0.00003264184,0.0006433584],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.00001359426,0.00001012848,0.05430864,0.000002307057,0.000009282177,0.00000291368,0.0003684005,0.0003890501,0.00001440639,0.9428458,0.00008038976,0.001955051],"study_design_scores_gemma":[0.0004825431,0.001585747,0.7231535,0.00001814169,0.0000168023,0.0001718021,0.001033703,0.02639694,0.0001010436,0.2355411,0.01113651,0.0003621537],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9562418,0.0001397606,0.001498621,0.03721668,0.0001096402,0.00003565783,0.00002080488,0.000005100779,0.004731974],"genre_scores_gemma":[0.9933758,0.00002106287,0.0003795448,0.005967429,0.0002347217,5.041554e-7,1.905597e-7,0.000004008899,0.0000167897],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7073048,"threshold_uncertainty_score":0.6908402,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05906667972576887,"score_gpt":0.2806846261848037,"score_spread":0.2216179464590348,"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."}}