{"id":"W1602895485","doi":"10.2139/ssrn.2269779","title":"An Analysis of the Determinants of S&P Ratings Assigned to Canadian Firms: Application of a Multinomial Logit","year":2013,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Credit Risk and Financial Regulations","field":"Economics, Econometrics and Finance","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université Laval","funders":"","keywords":"Multinomial logistic regression; Logit; Multinomial distribution; Logistic regression; Econometrics; Economics; Actuarial science; Statistics; Financial economics; Business; Mathematics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007053197,0.00008258181,0.0003621207,0.0004706471,0.0001030026,0.00001549877,0.0003370601,0.0000735551,0.00004623402],"category_scores_gemma":[0.0001647525,0.00007393653,0.0001898325,0.0007331625,0.00004923806,0.0001272688,0.00001707984,0.0002203966,0.00001051232],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003955282,"about_ca_system_score_gemma":0.000583649,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.1403735,"about_ca_topic_score_gemma":0.4971142,"domain_scores_codex":[0.99853,0.00001822165,0.0006897371,0.000150662,0.00005135417,0.0005600317],"domain_scores_gemma":[0.998701,0.00002864395,0.0007420687,0.0003009865,0.0001375209,0.0000898069],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001128189,0.00006019503,0.9348351,0.000004036344,0.000137569,3.285582e-8,0.0005064305,0.001888147,0.0009205687,0.04556577,0.00002857969,0.01604231],"study_design_scores_gemma":[0.0002267989,0.0001247171,0.9592449,0.000005902361,0.0000697936,0.000002509764,0.0002394045,0.01144516,0.0002402313,0.02785689,0.000439065,0.0001045912],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.983954,0.0001556983,0.01517464,0.000194393,0.00005903245,0.0002178968,0.00007101853,0.000002289228,0.0001710574],"genre_scores_gemma":[0.9994567,0.00005820075,0.0002968109,0.00001327738,0.00004840094,0.00001301727,0.000005995013,0.000008553962,0.00009903548],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3567407,"threshold_uncertainty_score":0.8653508,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01220889358674962,"score_gpt":0.2336765013949846,"score_spread":0.221467607808235,"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."}}