{"id":"W3124510538","doi":"10.1111/poms.13348","title":"Blockchain Adoption for Combating Deceptive Counterfeits","year":2021,"lang":"en","type":"article","venue":"Production and Operations Management","topic":"Blockchain Technology Applications and Security","field":"Computer Science","cited_by":462,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"National Natural Science Foundation of China","keywords":"Counterfeit; Blockchain; Government (linguistics); Product (mathematics); Business; Enforcement; Quality (philosophy); Subsidy; Marketing; Regret; Computer security; Economics; Computer science; Law","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":[0.001833042,0.0004303827,0.0003696436,0.0006157717,0.0006048036,0.00135438,0.0006937723,0.0009028625,0.004453558],"category_scores_gemma":[0.009567606,0.0001400203,0.0003031225,0.000653765,0.0005016255,0.003184814,0.001488805,0.0009494468,0.0005478146],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007556576,"about_ca_system_score_gemma":0.001608724,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002363715,"about_ca_topic_score_gemma":0.003445994,"domain_scores_codex":[0.9986005,0.0005760809,0.00004766935,0.0001502025,0.0004065003,0.0002189845],"domain_scores_gemma":[0.9935327,0.003412317,0.001093076,0.000565302,0.0009974663,0.0003991124],"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":[0.0009871055,0.002336082,0.075909,0.001742332,0.0001988051,0.002201546,0.00369206,0.1472461,0.0310096,0.1367895,0.0102622,0.5876256],"study_design_scores_gemma":[0.0002563111,0.00319333,0.03058915,0.0007105626,0.0003285961,0.001100883,0.005616566,0.7984639,0.01754833,0.09418489,0.04783966,0.0001676589],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8797895,0.001990181,0.07433081,0.00357238,0.0001158893,0.0003678852,0.00013407,0.0002963088,0.039403],"genre_scores_gemma":[0.9943183,0.0004909136,0.003643517,0.00008173649,0.00001655633,0.00003409745,0.00003540046,0.000006961649,0.001372444],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004453558,"threshold_uncertainty_score":0.01489866,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01351661394206303,"score_gpt":0.2496239493197831,"score_spread":0.2361073353777201,"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."}}