{"id":"W2529751819","doi":"","title":"The missing credit information system in Hungary","year":2011,"lang":"en","type":"article","venue":"The Journal of Internet Banking and Commerce","topic":"Hungarian Social, Economic and Educational Studies","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Credit history; Profit (economics); Credit reference; Point (geometry); Portfolio; Credit risk; Credit enhancement; Business; Credit crunch; Credit card interest; Actuarial science; Finance; Financial system; Economics","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":[0.001815239,0.0001072068,0.0004305312,0.001096285,0.001297323,0.007332716,0.0008687621,0.0009883483,0.003145378],"category_scores_gemma":[0.003618662,0.0003404366,0.0002146516,0.001828048,0.002877424,0.002748445,0.002411925,0.001700325,0.0006575969],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005682928,"about_ca_system_score_gemma":0.005418582,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01013265,"about_ca_topic_score_gemma":0.002894698,"domain_scores_codex":[0.9979983,0.0002919075,0.0002391529,0.0003144984,0.0005817367,0.0005744244],"domain_scores_gemma":[0.9979383,0.0006441907,0.0005007572,0.0002169601,0.0003845147,0.0003153177],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.0005863875,0.0002135631,0.04633787,0.0006250518,0.00007860415,0.01065852,0.009661697,0.004174679,0.004084823,0.7015631,0.02214911,0.1998666],"study_design_scores_gemma":[0.0002753823,0.0002956512,0.2550655,0.0008778262,0.0001400648,0.006356957,0.01256453,0.01184153,0.01032538,0.08429257,0.6177261,0.0002383924],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8846496,0.006832871,0.006289005,0.01267494,0.0004384448,0.00009956174,0.001031579,0.0002579769,0.08772592],"genre_scores_gemma":[0.9933138,0.001120243,0.0007340729,0.0005829736,0.0000568173,0.0000130091,0.0002021741,0.00001729416,0.003959503],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01013265,"threshold_uncertainty_score":0.04123276,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04204756996837401,"score_gpt":0.2715021536362072,"score_spread":0.2294545836678332,"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."}}