{"id":"W7100030401","doi":"","title":"1 Regulations and Competition in Credit Card Market in Turkey","year":2015,"lang":"en","type":"article","venue":"","topic":"Research on Leishmaniasis Studies","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Credit card interest; Credit card; Credit history; Interest rate; Competition (biology); Credit crunch; Installment credit; Quarter (Canadian coin)","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":[0.0008310042,0.0001333185,0.0003510996,0.0009158175,0.0005696825,0.002618301,0.0003701822,0.0006385485,0.005106604],"category_scores_gemma":[0.003206556,0.0001534617,0.0002358049,0.001502596,0.0007962837,0.0006418405,0.0003774133,0.000571779,0.0005723234],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002267811,"about_ca_system_score_gemma":0.001658429,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0261517,"about_ca_topic_score_gemma":0.01896051,"domain_scores_codex":[0.9988961,0.0002473475,0.00009855755,0.0002028168,0.0002907085,0.0002644586],"domain_scores_gemma":[0.9939048,0.001341196,0.003708535,0.000128393,0.0006287292,0.000288298],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005968683,0.0007033052,0.8874057,0.0002717515,0.00009744301,0.002126471,0.002104783,0.007199009,0.00224104,0.04348137,0.01483573,0.03893647],"study_design_scores_gemma":[0.00003844807,0.0001826496,0.9758942,0.00007066275,0.00004280451,0.0003211842,0.002015712,0.006146554,0.0005260915,0.003413881,0.01130012,0.00004752781],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9789315,0.0008679259,0.0003156017,0.0007365752,0.00001640855,0.00002924761,0.0007766538,0.00002052219,0.01830546],"genre_scores_gemma":[0.9983291,0.000179636,0.00008752161,0.00006623373,0.00001270008,0.000004652573,0.0003042768,0.000002309398,0.001013659],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0261517,"threshold_uncertainty_score":0.05199897,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05388363659912357,"score_gpt":0.3269101790941274,"score_spread":0.2730265424950038,"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."}}