{"id":"W4392742050","doi":"10.1017/flw.2024.2","title":"Crypto and financial literacy of cryptoasset owners versus non-owners: The role of gender differences","year":2023,"lang":"en","type":"article","venue":"Journal of Financial Literacy and Wellbeing","topic":"Financial Literacy, Pension, Retirement Analysis","field":"Business, Management and Accounting","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Bank of Canada; York University","funders":"Università degli Studi di Urbino Carlo Bo; Université d'Orléans; York University","keywords":"Financial literacy; Microdata (statistics); Literacy; Business; Cryptocurrency; Accounting; Finance; Economics; Economic growth; Demography; Sociology; Computer science; Computer security; Census","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001056522,0.0003267316,0.0007504221,0.0007667536,0.0003333875,0.0003019604,0.0004060273,0.0001409064,0.00005474256],"category_scores_gemma":[0.0008642421,0.0002250792,0.0003043273,0.00131265,0.0002139031,0.00208788,0.0002848641,0.0003544594,0.000008888282],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002134246,"about_ca_system_score_gemma":0.000104027,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002065058,"about_ca_topic_score_gemma":0.00001989133,"domain_scores_codex":[0.9973879,0.00004858957,0.001239372,0.0003030511,0.0006114551,0.0004095574],"domain_scores_gemma":[0.99721,0.0003956877,0.001483157,0.0002516769,0.0006162816,0.00004319242],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001956381,0.0002209791,0.8783192,0.0008419275,0.00009667687,0.0000930345,0.006814476,0.00008117806,0.005369916,0.02926634,0.002210456,0.07472945],"study_design_scores_gemma":[0.002024481,0.000184611,0.9312285,0.0007845289,0.0004090328,0.00000906821,0.0004551008,0.00373248,0.0005894591,0.01926128,0.0408818,0.0004396803],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9971016,0.001177579,0.00008135341,0.0002155932,0.0006665547,0.0001658573,0.00001404878,0.00001630449,0.0005610952],"genre_scores_gemma":[0.9973612,0.000398547,0.0004953438,0.0002571548,0.001380269,0.00000450683,0.00001489897,0.00002426213,0.00006381882],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07428977,"threshold_uncertainty_score":0.9178464,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01229554182845954,"score_gpt":0.2421977572635192,"score_spread":0.2299022154350596,"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."}}