{"id":"W4323045013","doi":"10.1093/jcr/ucad014","title":"Machine Talk: How Verbal Embodiment in Conversational AI Shapes Consumer–Brand Relationships","year":2023,"lang":"en","type":"article","venue":"Journal of Consumer Research","topic":"Media Influence and Health","field":"Arts and Humanities","cited_by":148,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Social Sciences and Humanities Research Council; Canada Research Chairs; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung","keywords":"Perception; Interface (matter); Psychology; Loyalty; Advertising; Brand management; Brand loyalty; Conceptual model; Social psychology; Cognitive psychology; Business; Marketing; Computer science","routes":{"ca_aff":true,"ca_fund":true,"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":[0.002024401,0.0002418705,0.0001335082,0.0005576547,0.0005797703,0.00466899,0.0003855816,0.0007979943,0.004704048],"category_scores_gemma":[0.01718094,0.0003032997,0.0002238426,0.0002908638,0.001673631,0.002271557,0.001588623,0.0007638478,0.0004089031],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006126334,"about_ca_system_score_gemma":0.0003452902,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001269531,"about_ca_topic_score_gemma":0.001008261,"domain_scores_codex":[0.9983733,0.0009592419,0.00004393447,0.0002176322,0.0003068354,0.00009912662],"domain_scores_gemma":[0.9921798,0.00551554,0.001161256,0.0004128314,0.0004006874,0.0003298458],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00273121,0.0009904795,0.2524052,0.001262123,0.0004903267,0.001454804,0.2259643,0.008841326,0.1661915,0.08691141,0.003127955,0.2496294],"study_design_scores_gemma":[0.0001977951,0.001594199,0.6686968,0.0006302596,0.0007086023,0.001596819,0.0837571,0.05659489,0.02677245,0.1156717,0.04338536,0.000393971],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9608788,0.0002800914,0.01052193,0.0004947189,0.00002971841,0.00003044313,0.00004125623,0.00007114575,0.02765194],"genre_scores_gemma":[0.9963857,0.00007738132,0.002421114,0.0001030524,0.00001214405,0.00002028328,0.00001981325,0.00002397776,0.0009365899],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004704048,"threshold_uncertainty_score":0.01573664,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2426835687121139,"score_gpt":0.3965617826035696,"score_spread":0.1538782138914556,"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."}}