{"id":"W4416364204","doi":"10.5937/sjm20-56002","title":"Towards deciphering the crypto-shopper: An analysis on knowledge and preferences of consumers using cryptocurrencies for purchases","year":2025,"lang":"en","type":"article","venue":"Serbian Journal of Management","topic":"Blockchain Technology Applications and Security","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Purchasing; Cryptocurrency; Cluster (spacecraft); Regression analysis; Domain (mathematical analysis)","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":[0.0006312302,0.00009896796,0.0001823864,0.0007743196,0.0003231209,0.0006983312,0.0001329814,0.0004182914,0.003004689],"category_scores_gemma":[0.002341104,0.00009748356,0.0002304944,0.0006795751,0.0003201823,0.0008200532,0.0003935656,0.0004316033,0.0004001561],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002465829,"about_ca_system_score_gemma":0.000288659,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003923697,"about_ca_topic_score_gemma":0.004193736,"domain_scores_codex":[0.9997281,0.00009605931,0.00001844926,0.00002676537,0.00007429297,0.00005634824],"domain_scores_gemma":[0.998197,0.0009291839,0.000395279,0.00007036479,0.0002237673,0.0001844366],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002008474,0.0002639244,0.9473467,0.00009147744,0.00003286016,0.0005340353,0.0253126,0.00008117176,0.001318135,0.0001783625,0.0003188929,0.02432099],"study_design_scores_gemma":[0.000005063644,0.0002232364,0.9463117,0.0000459167,0.00002548887,0.0006888818,0.04993438,0.0005845386,0.0003512448,0.0001781508,0.001634236,0.00001724374],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9995282,0.00002912062,0.00004243374,0.00003587956,4.827767e-7,0.000002977146,0.00003039812,4.838894e-7,0.0003299995],"genre_scores_gemma":[0.9994199,0.00007649893,0.00007272411,0.00003129131,0.000001807106,0.000003975422,0.00006409353,7.66873e-7,0.0003289859],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003923697,"threshold_uncertainty_score":0.01005173,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02851426141023765,"score_gpt":0.3102262949636686,"score_spread":0.2817120335534309,"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."}}