{"id":"W4380366018","doi":"10.2298/csis220308039s","title":"Comprehensive risk assessment and analysis of blockchain technology implementation using fuzzy cognitive mapping","year":2023,"lang":"en","type":"article","venue":"Computer Science and Information Systems","topic":"Cognitive Science and Mapping","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Blockchain; Computer science; Delphi method; Fuzzy cognitive map; Risk analysis (engineering); Investment (military); Field (mathematics); Fuzzy logic; Resource (disambiguation); Knowledge management; Fuzzy set; Computer security; Business; Artificial intelligence; Fuzzy number","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":[0.003652528,0.0008733889,0.0005899399,0.005378794,0.001052379,0.001964098,0.0007037813,0.0008294244,0.001405544],"category_scores_gemma":[0.006901047,0.0003042801,0.001211855,0.001844056,0.0005626466,0.002078039,0.001285893,0.00045805,0.00007596291],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002194283,"about_ca_system_score_gemma":0.002307474,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01033106,"about_ca_topic_score_gemma":0.005972231,"domain_scores_codex":[0.9982302,0.0005522913,0.0001120501,0.0001248765,0.0007865297,0.0001940514],"domain_scores_gemma":[0.9966438,0.001909003,0.0004087065,0.0001178158,0.0008177173,0.0001029373],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003735755,0.0002447526,0.03912209,0.0005472668,0.0003083924,0.00084563,0.002221779,0.7810034,0.006110436,0.02748242,0.001094582,0.1406457],"study_design_scores_gemma":[0.00001484573,0.0001339378,0.00800522,0.00005640507,0.00009205106,0.000145748,0.00112405,0.974375,0.002145229,0.01306503,0.0007888595,0.00005363676],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6199422,0.0006416602,0.368217,0.0004226797,0.00002728522,0.0004144698,0.0001822481,0.0001693926,0.009983013],"genre_scores_gemma":[0.9763067,0.0002278131,0.02260143,0.00001123628,0.000005093792,0.000100892,0.00007574295,0.000004980409,0.0006660408],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01033106,"threshold_uncertainty_score":0.02054185,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03520294052963371,"score_gpt":0.3273525612565306,"score_spread":0.2921496207268969,"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."}}