{"id":"W2009411066","doi":"10.1111/j.1540-6288.2001.tb00011.x","title":"Combining Bond Rating Forecasts Using Logit","year":2001,"lang":"en","type":"article","venue":"Financial Review","topic":"Credit Risk and Financial Regulations","field":"Economics, Econometrics and Finance","cited_by":108,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Econometrics; Competitor analysis; Logit; Logistic regression; Bond; Bond credit rating; Yield (engineering); Ordered logit; Statistics; Economics; Actuarial science; Mathematics; Finance","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004671109,0.0007872465,0.001040296,0.002706622,0.0003029327,0.001463489,0.0007478035,0.0006704965,0.005703175],"category_scores_gemma":[0.01841975,0.0004941141,0.0009404016,0.001797945,0.0001558734,0.001384341,0.0007329845,0.0009465182,0.001999425],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006035733,"about_ca_system_score_gemma":0.0004775351,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01307254,"about_ca_topic_score_gemma":0.01313138,"domain_scores_codex":[0.9975382,0.001179381,0.0001465995,0.0003265792,0.0006760145,0.0001332259],"domain_scores_gemma":[0.9904551,0.006430214,0.0006993557,0.0006199424,0.001606149,0.0001892509],"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":[0.0004939805,0.0002295682,0.05869072,0.00009057569,0.0004572107,0.0001949813,0.00007688804,0.6799093,0.001391872,0.002632166,0.006428036,0.2494047],"study_design_scores_gemma":[0.00002074451,0.00005035839,0.007774756,0.000007418264,0.00003759366,0.00002477957,0.0000206424,0.9880037,0.0006306297,0.002779018,0.0006166333,0.00003372173],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4537429,0.0007615122,0.5238624,0.001023698,0.0002304627,0.0002785731,0.004256766,0.003260627,0.01258299],"genre_scores_gemma":[0.9421818,0.0001981494,0.05229117,0.00006921559,0.0001180798,0.00007769889,0.001896693,0.00004696954,0.003120416],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01307254,"threshold_uncertainty_score":0.02599293,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1025977363133566,"score_gpt":0.2834348959084037,"score_spread":0.1808371595950471,"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."}}