{"id":"W2906494638","doi":"10.2139/ssrn.3224748","title":"Credit Market Segmentation and Capital Structure Stability","year":2018,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Corporate Finance and Governance","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Concordia University","funders":"","keywords":"Market segmentation; Stability (learning theory); Capital structure; Segmentation; Business; Financial stability; Financial system; Economics; Finance; Artificial intelligence; Computer science; Debt; Machine learning; Marketing","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":[0.0008911908,0.0001156634,0.0003496254,0.001293186,0.0008963647,0.003563715,0.0003163012,0.001251652,0.01335892],"category_scores_gemma":[0.009331055,0.0001881238,0.0002373187,0.00149524,0.001407398,0.002777846,0.0009864907,0.0009872143,0.0008628482],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00126858,"about_ca_system_score_gemma":0.0005633987,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005006003,"about_ca_topic_score_gemma":0.005902162,"domain_scores_codex":[0.9996693,0.0000689288,0.00002096588,0.00009412021,0.00004300959,0.0001037004],"domain_scores_gemma":[0.9902909,0.003345192,0.00326063,0.0004272601,0.000573408,0.002102622],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001466979,0.0003702111,0.891974,0.00003636027,0.0001425135,0.0004051891,0.002090711,0.004533454,0.002710866,0.06272832,0.00403605,0.02950534],"study_design_scores_gemma":[0.0000641579,0.0001165406,0.9130382,0.00002508162,0.00004519082,0.0001821112,0.001456236,0.008510702,0.0005952796,0.07335944,0.002586403,0.00002065333],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9881644,0.0003793675,0.0008265935,0.000896165,0.00001118744,0.000009207273,0.0001388046,0.00001689524,0.009557278],"genre_scores_gemma":[0.9987796,0.00003686476,0.00005431771,0.00003627115,0.00002240817,0.000001513922,0.00008096512,0.000004535773,0.0009835536],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01335892,"threshold_uncertainty_score":0.04469001,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006568227055652923,"score_gpt":0.1969312083061795,"score_spread":0.1903629812505266,"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."}}