{"id":"W2931173859","doi":"10.1002/itl2.100","title":"Comparative evaluation of consensus mechanisms in cryptocurrencies","year":2019,"lang":"en","type":"article","venue":"Internet Technology Letters","topic":"Blockchain Technology Applications and Security","field":"Computer Science","cited_by":33,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Cryptocurrency; Computer science; Mechanism (biology); Incentive; Proof-of-work system; Set (abstract data type); Consensus; Consensus algorithm; Computer security; Data science; Artificial intelligence; Multi-agent system; Economics; Microeconomics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000520887,0.0001205622,0.0002624746,0.000655963,0.00001419752,0.00001099367,0.001005403,0.0001975533,0.00002776448],"category_scores_gemma":[0.00003181469,0.0001211757,0.00003606856,0.0007727262,0.000239943,0.00006274603,0.0002672216,0.0002977183,0.00008063471],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007888246,"about_ca_system_score_gemma":0.00003883812,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002599986,"about_ca_topic_score_gemma":0.00003540785,"domain_scores_codex":[0.9988699,0.00006947722,0.0002964536,0.0003691437,0.0001913356,0.0002036848],"domain_scores_gemma":[0.9989541,0.00006324198,0.0001595018,0.0006563254,0.0001527768,0.00001407212],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000004090595,0.00008026017,0.002541466,0.000008453587,0.00002722731,0.000002748096,0.0005562377,0.0001414517,0.05947111,0.9311005,0.0006427087,0.005423691],"study_design_scores_gemma":[0.001314077,0.0001762544,0.002565296,0.00007342236,0.00001705876,0.0000448589,0.0004425838,0.2349024,0.3288583,0.43051,0.0007728243,0.0003230304],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8738815,0.000116157,0.1161173,0.008290406,0.0001199661,0.0004680938,0.000001139123,0.0002316493,0.0007738502],"genre_scores_gemma":[0.9880083,0.00000114292,0.01159311,0.0002712382,0.000002175116,0.0001101252,0.000001283813,0.00000371264,0.000008924971],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5005906,"threshold_uncertainty_score":0.4941401,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02322543217386045,"score_gpt":0.278372764180799,"score_spread":0.2551473320069386,"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."}}