{"id":"W4388095418","doi":"10.1002/mar.21935","title":"What is driving consumer resistance to crypto‐payment? A multianalytical investigation","year":2023,"lang":"en","type":"article","venue":"Psychology and Marketing","topic":"Digital Marketing and Social Media","field":"Social Sciences","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"Social Sciences and Humanities Research Council of Canada; Natural Sciences and Engineering Research Council of Canada","keywords":"Cryptocurrency; Payment; Mainstream; Context (archaeology); Resistance (ecology); Business; Consumer behaviour; Empirical research; Marketing; Advertising; Computer security; Computer science; Law; Biology; Ecology; Finance","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003986713,0.00009615043,0.0001464893,0.0001138449,0.0005459274,0.0002053212,0.0001261727,0.0001336148,0.00008870505],"category_scores_gemma":[0.004207146,0.0001044306,0.00003738248,0.0005432484,0.0003783631,0.0002720476,0.00005805401,0.0001385124,0.0001296864],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002318506,"about_ca_system_score_gemma":0.00003850438,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000265236,"about_ca_topic_score_gemma":0.0003965362,"domain_scores_codex":[0.9983789,0.0004383862,0.0001984382,0.0003506414,0.0002184593,0.0004152256],"domain_scores_gemma":[0.9981059,0.001406754,0.00005925214,0.0001198022,0.00006149181,0.0002467344],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004245142,0.00007273715,0.3075593,0.000113977,0.0001261921,0.00005824234,0.09552674,7.430405e-7,0.001227161,0.009506263,0.243811,0.3415731],"study_design_scores_gemma":[0.000615187,0.00003035383,0.3819675,0.0006388042,0.00003778715,0.000001419378,0.02224263,0.00004776673,0.00004222435,0.01321958,0.5806644,0.0004923941],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8823312,0.0003531807,0.00002354385,0.04099705,0.001111119,0.000214488,0.000002261983,0.000212668,0.07475446],"genre_scores_gemma":[0.9835917,0.001611256,0.0004985557,0.004453564,0.0002373574,0.00003210504,0.000003707123,0.00001445064,0.009557336],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3410807,"threshold_uncertainty_score":0.5036651,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0318568846867352,"score_gpt":0.3598542198324827,"score_spread":0.3279973351457475,"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."}}