{"id":"W4246436249","doi":"10.2139/ssrn.1786443","title":"Do Firms Have a Target Leverage? Evidence from Credit Markets","year":2010,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Banking stability, regulation, efficiency","field":"Economics, Econometrics and Finance","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Leverage (statistics); Business; Financial system; Monetary economics; Economics; Computer science; Artificial intelligence","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":[0.003179166,0.000243241,0.0006322364,0.001473502,0.0007023203,0.003157327,0.0009846387,0.002688306,0.010593],"category_scores_gemma":[0.0376398,0.0002985331,0.0003612901,0.002491872,0.001824483,0.003472665,0.001378413,0.0016574,0.001183498],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003995447,"about_ca_system_score_gemma":0.0003699548,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005068496,"about_ca_topic_score_gemma":0.005245824,"domain_scores_codex":[0.9985272,0.000382845,0.0001561708,0.0002428503,0.000357186,0.0003336613],"domain_scores_gemma":[0.858631,0.06489283,0.06148285,0.005347367,0.004393071,0.005252869],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001136064,0.0003723928,0.9734669,0.00008850904,0.0002472662,0.0004385579,0.0006000865,0.0003868083,0.0004685957,0.005666745,0.002375077,0.01475291],"study_design_scores_gemma":[0.000182565,0.0001973868,0.9896427,0.00005745857,0.0001907326,0.0003466173,0.00085628,0.0009054139,0.0005172159,0.00461878,0.002463733,0.00002113307],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9825826,0.001803108,0.0004060172,0.003606909,0.00002172511,0.00001340576,0.0006879049,0.00001597098,0.01086239],"genre_scores_gemma":[0.9989008,0.0003385921,0.00002115176,0.0001796629,0.00004847941,0.000002439362,0.0001885573,0.000002268862,0.0003180524],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.010593,"threshold_uncertainty_score":0.03543711,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01629889793956082,"score_gpt":0.2308238235388417,"score_spread":0.2145249255992809,"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."}}