{"id":"W3001002818","doi":"10.3390/jrfm13020020","title":"Credit Spreads, Business Conditions, and Expected Corporate Bond Returns","year":2020,"lang":"en","type":"article","venue":"Journal of risk and financial management","topic":"Credit Risk and Financial Regulations","field":"Economics, Econometrics and Finance","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Natural Science Foundation of China; National Science Foundation","keywords":"Predictability; Predictive power; Bond; Index (typography); Corporate bond; Credit default swap index; Economics; Credit spread (options); Econometrics; Bond market; Credit risk; Investment (military); Financial economics; Monetary economics; Credit valuation adjustment; Business; Actuarial science; Finance; Mathematics; Statistics; Computer science; Credit reference","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002895401,0.0001579216,0.0004459248,0.0002395532,0.0001933334,0.00009288496,0.0001268043,0.00008688324,0.00004278057],"category_scores_gemma":[0.0002780347,0.0001653289,0.00008231126,0.000453153,0.00009873198,0.0002879697,0.00008757418,0.0002148448,0.00001844283],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002778377,"about_ca_system_score_gemma":0.00002168562,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004161179,"about_ca_topic_score_gemma":0.00001764354,"domain_scores_codex":[0.9987545,0.00001253696,0.0007285944,0.000243982,0.00007339476,0.0001870088],"domain_scores_gemma":[0.9985684,0.00003706992,0.0009994423,0.0001184116,0.000105579,0.0001710935],"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":[0.0003789215,0.0002069303,0.4061177,0.0001592215,0.0001050835,0.0002623535,0.003466826,0.0001423718,0.00002859931,0.5062076,0.03904368,0.04388066],"study_design_scores_gemma":[0.0009753715,0.000121846,0.824306,0.00003375446,0.00004664811,0.00001528008,0.0001928564,0.0001207017,0.000006218503,0.0339493,0.1400504,0.0001816382],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9546672,0.005394245,0.03578207,0.001274044,0.0007690617,0.0002326103,0.0003259973,0.00002269217,0.001532063],"genre_scores_gemma":[0.9874511,0.009432437,0.002151708,0.0001258365,0.0007143701,0.000005248165,0.00001334257,0.00001621383,0.0000897754],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4722583,"threshold_uncertainty_score":0.6741917,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02419982483146387,"score_gpt":0.2010780378350826,"score_spread":0.1768782130036187,"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."}}