{"id":"W2100202799","doi":"10.2139/ssrn.2509366","title":"The Determinants of Long-Term Japanese Government Bondss Low Nominal Yields","year":2014,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Credit Risk and Financial Regulations","field":"Economics, Econometrics and Finance","cited_by":7,"is_retracted":false,"has_abstract":false,"ca_institutions":"Mount Royal University","funders":"","keywords":"Term (time); Government (linguistics); Economics; Econometrics; Linguistics; Physics; Philosophy","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":[0.001789254,0.0001354595,0.0002899,0.00005356362,0.0003389548,0.00006352246,0.0003768381,0.00008691608,0.00002873826],"category_scores_gemma":[0.000184437,0.0001146019,0.0001841124,0.0001210025,0.00009210364,0.0001354491,0.00004779653,0.0006174264,0.00005769771],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004892598,"about_ca_system_score_gemma":0.0001793801,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008823736,"about_ca_topic_score_gemma":0.001811354,"domain_scores_codex":[0.997892,0.00001976182,0.0006491762,0.0001869101,0.0001052575,0.001146899],"domain_scores_gemma":[0.9989364,0.00009725231,0.0005793496,0.0002837178,0.00003449253,0.00006877819],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00008251519,0.0001155883,0.5535912,0.00001257195,0.00006666438,0.000002245688,0.0003083136,0.00003478712,0.00004262287,0.3622591,0.00007245391,0.08341189],"study_design_scores_gemma":[0.001108711,0.0006526692,0.8606609,0.00004289276,0.00002684851,0.0002331296,0.0004426505,0.001799403,0.000243847,0.1296363,0.0047898,0.0003628463],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.990856,0.002319334,0.003993524,0.0002562598,0.0004719867,0.00009202128,0.00001539958,0.000006839231,0.001988642],"genre_scores_gemma":[0.9946672,0.002223676,0.00001892486,0.00001209112,0.0004087208,0.000006371866,0.000001308382,0.00001834244,0.002643323],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3070697,"threshold_uncertainty_score":0.4673332,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00933863294736163,"score_gpt":0.2137756438675894,"score_spread":0.2044370109202278,"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."}}