{"id":"W4414498208","doi":"10.1016/j.jretconser.2025.104486","title":"Virtual characters, virtual influence? Assessing the efficacy of virtual and human influencers and the influence of need for interaction and consumer envy","year":2025,"lang":"en","type":"article","venue":"Journal of Retailing and Consumer Services","topic":"Media Influence and Health","field":"Arts and Humanities","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Influencer marketing; Credibility; Perception; Affect (linguistics); Human interaction; Field (mathematics); Consumer behaviour","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002573503,0.0002586981,0.0002291005,0.0006800467,0.0004948093,0.001913392,0.0002503294,0.0007213717,0.003240855],"category_scores_gemma":[0.0136197,0.000207105,0.0003575633,0.0002334324,0.001156458,0.0009959989,0.0008518147,0.0005851572,0.0002728709],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002204148,"about_ca_system_score_gemma":0.0002370924,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007351156,"about_ca_topic_score_gemma":0.001022164,"domain_scores_codex":[0.9979268,0.001196988,0.0001226552,0.0001714693,0.0004337496,0.0001482827],"domain_scores_gemma":[0.9861924,0.007750968,0.003426544,0.0008006381,0.0005803549,0.001249115],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001541639,0.002245256,0.929098,0.0003101535,0.0002504634,0.0001931065,0.0156648,0.0002805614,0.007195077,0.002211478,0.0003161074,0.0406934],"study_design_scores_gemma":[0.00005441558,0.001573898,0.9798956,0.00007150741,0.0002035258,0.0002225548,0.01252481,0.001350565,0.001631779,0.0009323475,0.001500219,0.00003881233],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9953033,0.00008784726,0.0002084249,0.00005164914,0.000007252902,0.0000281558,0.000009524354,0.000002729338,0.004301132],"genre_scores_gemma":[0.9993333,0.00004775358,0.0001963738,0.00002662847,0.000007145212,0.0000203635,0.00001077266,0.000001307521,0.0003563198],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003240855,"threshold_uncertainty_score":0.01361018,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01796038810622915,"score_gpt":0.2987878151396771,"score_spread":0.280827427033448,"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."}}