{"id":"W1982759367","doi":"10.1080/17446540500474227","title":"A nonparametric cointegration analysis of the forward rate unbiasedness hypothesis","year":2006,"lang":"en","type":"article","venue":"Applied Financial Economics Letters","topic":"Monetary Policy and Economic Impact","field":"Economics, Econometrics and Finance","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Cointegration; Nonparametric statistics; Econometrics; Economics; Us dollar; Statistical hypothesis testing; Inference; Statistics; Mathematics; Exchange rate; Computer science; Macroeconomics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0006440436,0.0002796695,0.0009059607,0.0008493639,0.0001641971,0.00007472213,0.0004853556,0.0001598948,0.0001746418],"category_scores_gemma":[0.0001074148,0.0002879204,0.0005927801,0.001088043,0.000167215,0.0001878962,0.00006445375,0.0001819762,0.0002031279],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002772218,"about_ca_system_score_gemma":0.00003024562,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002778401,"about_ca_topic_score_gemma":0.0006616697,"domain_scores_codex":[0.9977492,0.00002015439,0.001220211,0.0005421573,0.00002454388,0.0004437119],"domain_scores_gemma":[0.9979854,0.0002251795,0.001042472,0.0006773654,0.000008715057,0.00006093138],"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":[0.0001392387,0.0002093141,0.07458606,0.00003155631,0.0008551208,0.000001192119,0.0003284802,0.3075253,0.0009080991,0.6051334,0.008339285,0.001942912],"study_design_scores_gemma":[0.001173395,0.00003089129,0.9042667,0.000007276715,0.000378046,0.000001603014,0.00002599184,0.03408841,0.002589934,0.04242659,0.01422496,0.0007861715],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9847385,0.00006005569,0.004052644,0.001303377,0.0004252052,0.0003380999,0.0005356177,0.00002366557,0.008522872],"genre_scores_gemma":[0.9959658,0.00003448916,0.0005599298,0.002962396,0.0001831821,0.00004654792,0.00005743984,0.00003165617,0.0001585414],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8296807,"threshold_uncertainty_score":0.9999573,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02442470571319327,"score_gpt":0.1757004892823036,"score_spread":0.1512757835691104,"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."}}