{"id":"W3111596125","doi":"10.3390/jrfm13120317","title":"A System to Support the Transparency of Consumer Credit Offers","year":2020,"lang":"en","type":"article","venue":"Journal of risk and financial management","topic":"Financial Literacy, Pension, Retirement Analysis","field":"Business, Management and Accounting","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Transparency (behavior); Financial literacy; Credit reference; Intermediary; Business; Credit enhancement; Interest rate; Credit card interest; Credit history; Finance; Actuarial science; Marketing; Computer science; Credit risk; Computer security","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006659909,0.0001846756,0.0004592248,0.0002777264,0.0001672819,0.00009483114,0.0003640757,0.00004433483,0.00007615938],"category_scores_gemma":[0.0001584221,0.0001294946,0.0002197148,0.0007575242,0.00005958505,0.0003652341,0.0001422213,0.0001687379,0.0000442911],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002220201,"about_ca_system_score_gemma":0.00002321033,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001225435,"about_ca_topic_score_gemma":0.00003608317,"domain_scores_codex":[0.9982281,0.00002278104,0.0008270518,0.0001968361,0.0005091962,0.0002159965],"domain_scores_gemma":[0.998745,0.00003608552,0.0007357652,0.0001705379,0.000270423,0.00004219705],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001566994,0.0002418634,0.7820551,0.002303172,0.0001530654,0.0003847354,0.002707332,0.0006047305,0.0001533805,0.05628049,0.06223663,0.09131255],"study_design_scores_gemma":[0.001625061,0.0002629088,0.3962672,0.0003468942,0.001495703,0.000005862985,0.001354285,0.0006852627,0.00004349522,0.0004412758,0.5971248,0.0003472604],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9896307,0.0004072954,0.005611193,0.0007660923,0.0006709069,0.0004888709,0.00001793347,0.00002673681,0.002380291],"genre_scores_gemma":[0.9972073,0.0002709872,0.0004073044,0.001185593,0.0008723228,0.000005262372,0.000003199684,0.00001506223,0.00003291369],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5348881,"threshold_uncertainty_score":0.5280635,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01276430082019174,"score_gpt":0.2062253813741655,"score_spread":0.1934610805539738,"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."}}