{"id":"W4402676310","doi":"10.2139/ssrn.4932810","title":"The Rise of Central Bank Digital Currencies: Exploring Adoption Determinants and Early Macroeconomic and Well-being Impacts","year":2024,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Economic Growth and Development","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Digital currency; Central bank; Economics; Monetary economics; Business; Financial system; Monetary policy; Currency","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.001027891,0.0002569648,0.0002896723,0.0001626069,0.000224013,0.001176003,0.0005982362,0.00008915502,7.544736e-7],"category_scores_gemma":[0.00002768895,0.0002025545,0.0001052569,0.00005853661,0.00008493254,0.0006365463,0.001141703,0.001725554,0.00000809581],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007163943,"about_ca_system_score_gemma":0.001932185,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003877868,"about_ca_topic_score_gemma":0.0001113376,"domain_scores_codex":[0.9972746,0.00003497981,0.000550666,0.0004119393,0.0001268108,0.001601016],"domain_scores_gemma":[0.9991227,0.00007884933,0.0003307881,0.00025513,0.00003717671,0.0001753411],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00006330076,0.00003567933,0.116008,0.0002914893,0.0004443163,0.00002764599,0.00759796,0.00008137157,0.00004118272,0.128369,0.00003913753,0.7470009],"study_design_scores_gemma":[0.0007021501,0.0003233952,0.0600207,0.0007129,0.0000591434,0.001179903,0.001230107,0.008037067,0.0004121743,0.9258834,0.00073817,0.0007009467],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9814828,0.01389128,0.00291245,0.0001964172,0.001056341,0.0001460525,0.000002033577,0.00002772618,0.0002849001],"genre_scores_gemma":[0.9757944,0.02377338,0.0001676117,0.000006023686,0.0001501545,0.00001003572,4.77712e-7,0.00001612961,0.00008177052],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7975143,"threshold_uncertainty_score":0.9998609,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01030788922197489,"score_gpt":0.2149356597392049,"score_spread":0.20462777051723,"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."}}