{"id":"W3123754843","doi":"","title":"Credit Provision Strategy During Financial Crisis Using Bank Accounting Data","year":2016,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Banking stability, regulation, efficiency","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Loan; Credit crunch; Financial crisis; Financial system; Interest rate; Business; Term loan; Soft loan; Quarter (Canadian coin); Monetary economics; Finance; Economics; Non-performing loan; Non-conforming loan; Macroeconomics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009897343,0.000234062,0.0002794474,0.003818689,0.0001421876,0.001147769,0.0002454289,0.0003888302,0.001774325],"category_scores_gemma":[0.005010617,0.0001243158,0.000260693,0.003837311,0.0001740846,0.0006584834,0.0005971902,0.0002985337,0.0007695701],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006745632,"about_ca_system_score_gemma":0.0004650098,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01531103,"about_ca_topic_score_gemma":0.007013174,"domain_scores_codex":[0.9993777,0.0001697989,0.0001229096,0.0001224017,0.0001312237,0.00007609616],"domain_scores_gemma":[0.997554,0.0005787014,0.0009913103,0.0002008824,0.0005443826,0.0001306925],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002580834,0.0000623985,0.9506708,0.0001140026,0.0001282425,0.0003866316,0.0004757803,0.01136072,0.0007311847,0.0009294555,0.004704232,0.03017838],"study_design_scores_gemma":[0.00001651744,0.0000686916,0.9694223,0.00004700309,0.00005963107,0.0001809128,0.001005318,0.02076871,0.0006794103,0.0005560643,0.007172151,0.0000232806],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9870368,0.0003577076,0.0003679589,0.0001411814,0.000008019941,0.00003592873,0.009741015,0.00003892265,0.002272486],"genre_scores_gemma":[0.9922199,0.0002072759,0.000289033,0.00001024135,0.000006394791,0.00001482774,0.006721741,0.000004456665,0.000526128],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01531103,"threshold_uncertainty_score":0.03044385,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02790469921815784,"score_gpt":0.2492147125776638,"score_spread":0.221310013359506,"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."}}