{"id":"W7149296754","doi":"10.71465/ajainn672","title":"AI-Powered Personal Assistants: The Future of Customer Interaction","year":2025,"lang":"","type":"article","venue":"American Journal of Artificial Intelligence and Neural Networks","topic":"AI in Service Interactions","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Customer intelligence; Customer advocacy; Customer to customer; Voice of the customer; Customer retention; Customer relationship management; Natural (archaeology); Customer needs","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0007717165,0.0003815109,0.0007397687,0.0004029069,0.0003827504,0.0004353829,0.001264451,0.0001288856,0.0001344807],"category_scores_gemma":[0.00007262642,0.0002773112,0.0004346848,0.002198728,0.001216766,0.001219444,0.0003052705,0.001836361,0.000007811606],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001080792,"about_ca_system_score_gemma":0.0002261895,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000136557,"about_ca_topic_score_gemma":0.0001505322,"domain_scores_codex":[0.9962117,0.0005317953,0.001804231,0.0004224474,0.0005267481,0.0005030945],"domain_scores_gemma":[0.9953375,0.0009391445,0.002022664,0.0004421104,0.001068525,0.0001900184],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0007940141,0.0002299578,0.000467469,0.00001929863,0.0002805839,0.00003170633,0.003926553,0.01123208,0.0002211192,0.005453301,0.001111898,0.976232],"study_design_scores_gemma":[0.00006810654,0.001489018,0.0008720233,0.0005498189,0.0002485394,0.0003821507,0.03248687,0.9559498,0.001097588,0.002187916,0.00433964,0.0003284861],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1401507,0.007656046,0.7645389,0.06731521,0.01961194,0.0003448775,0.00001062652,0.00002532435,0.0003463741],"genre_scores_gemma":[0.9916081,0.002737667,0.0005048258,0.003712546,0.00136725,0.000002422811,6.846803e-7,0.00001583315,0.00005066508],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9759035,"threshold_uncertainty_score":0.9999679,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02121124867059681,"score_gpt":0.3142265458859868,"score_spread":0.2930152972153899,"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."}}