{"id":"W2344631104","doi":"10.5539/ijef.v8n5p151","title":"The Determinants of Credit Rationing in Tunisia: A Survey among Credit Managers","year":2016,"lang":"en","type":"article","venue":"International Journal of Economics and Finance","topic":"Banking stability, regulation, efficiency","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Credit rationing; Loan; Business; Credit history; Rationing; Adverse selection; Information asymmetry; Credit reference; Credit enhancement; Credit risk; Finance; Credit crunch; Actuarial science; Economics; Interest rate; Economic growth","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.0009064116,0.0001362299,0.000171871,0.0007128257,0.0005099486,0.0007427701,0.0002003097,0.0004705534,0.002300611],"category_scores_gemma":[0.002239034,0.0001902333,0.0001443457,0.001116891,0.0002677862,0.0005294658,0.0003453097,0.0004169245,0.000304102],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009393342,"about_ca_system_score_gemma":0.0005732493,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02980798,"about_ca_topic_score_gemma":0.02828147,"domain_scores_codex":[0.9995782,0.0001365745,0.00004953596,0.00004490729,0.00006030863,0.0001304331],"domain_scores_gemma":[0.997771,0.0004065826,0.001120589,0.00006160181,0.0002288486,0.0004113786],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003008753,0.00007509192,0.9940165,0.00001224814,0.00001304779,0.00008867901,0.001507335,0.00003974596,0.0002308406,0.0000459994,0.0002420645,0.003698236],"study_design_scores_gemma":[0.000003443115,0.00005727388,0.9958183,0.0000144803,0.000005427245,0.0000864465,0.003083156,0.0001494002,0.00004588018,0.00001674019,0.0007162362,0.000003335457],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9994076,0.00009984452,0.00001916271,0.0001671754,0.000001155083,0.00000474959,0.00007759158,7.038391e-7,0.0002219732],"genre_scores_gemma":[0.9994681,0.0001347151,0.00002821633,0.00005279227,0.000004923148,0.000005283434,0.00005070988,4.45135e-7,0.0002547989],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02980798,"threshold_uncertainty_score":0.05926895,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02247520728601817,"score_gpt":0.2367817443606102,"score_spread":0.214306537074592,"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."}}