{"id":"W4403484367","doi":"10.3390/jrfm17100470","title":"Enhancing Financial Advisory Services with GenAI: Consumer Perceptions and Attitudes Through Service-Dominant Logic and Artificial Intelligence Device Use Acceptance Perspectives","year":2024,"lang":"en","type":"article","venue":"Journal of risk and financial management","topic":"Technology Adoption and User Behaviour","field":"Decision Sciences","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Perception; Financial services; Service (business); Advisory committee; Service-dominant logic; Business; Marketing; Knowledge management; Finance; Psychology; Computer science; Economics; Management","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":[0.0009732482,0.000234549,0.0003900294,0.0004061227,0.0004155814,0.000550379,0.0002906885,0.0001302776,0.00005417839],"category_scores_gemma":[0.000200106,0.0001600103,0.00007098565,0.0006741778,0.0002634922,0.001073485,0.0002342367,0.0004432157,0.00001713438],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003858891,"about_ca_system_score_gemma":0.00006343402,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000653871,"about_ca_topic_score_gemma":0.00159485,"domain_scores_codex":[0.9980016,0.00008770043,0.0006731333,0.0004999468,0.000487264,0.0002503145],"domain_scores_gemma":[0.9987428,0.0002965453,0.0003159588,0.0002174262,0.0003321448,0.00009515389],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0007988858,0.0004154725,0.1682937,0.0004590341,0.0001140987,0.0007771656,0.0349287,0.0001012344,0.0007055157,0.1289232,0.0003340542,0.6641489],"study_design_scores_gemma":[0.0003339891,0.0003409064,0.9155077,0.0005597937,0.0003042517,0.0002551152,0.03133272,0.0002569812,0.000134239,0.0390317,0.01157249,0.0003700747],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8995085,0.006787945,0.09244935,0.0007097842,0.0002720777,0.0001908763,0.00001930295,0.00002964706,0.00003253795],"genre_scores_gemma":[0.9736613,0.0107755,0.015078,0.000290351,0.0001158626,0.000007894814,5.113587e-7,0.00001191529,0.00005863454],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.747214,"threshold_uncertainty_score":0.6525031,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06300137367041549,"score_gpt":0.3472886847706653,"score_spread":0.2842873111002499,"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."}}