{"id":"W4287759470","doi":"10.48550/arxiv.2006.05808","title":"Adapting Workflow Management Systems to BFT Blockchains -- The YAWL\\n Example","year":2020,"lang":"","type":"preprint","venue":"arXiv (Cornell University)","topic":"Scientific Computing and Data Management","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Workflow; Computer science; Scalability; Workflow management system; Blockchain; Byzantine fault tolerance; Workflow engine; Consistency (knowledge bases); Atomicity; Soundness; Database; Proof of concept; Fault tolerance; Distributed computing; Database transaction; Computer security","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":[0.003693981,0.000400537,0.0004023887,0.000740191,0.001301945,0.003341558,0.001334624,0.001608309,0.002413709],"category_scores_gemma":[0.005528816,0.0005211398,0.0006511454,0.00122062,0.001807295,0.004682478,0.004686293,0.001833949,0.001318128],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002057456,"about_ca_system_score_gemma":0.002313588,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005624827,"about_ca_topic_score_gemma":0.004390098,"domain_scores_codex":[0.9978271,0.0007912435,0.0001538355,0.0002892842,0.000633464,0.0003051327],"domain_scores_gemma":[0.9978725,0.0005324925,0.0001162405,0.001024302,0.00027268,0.0001818782],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003850154,0.0003759789,0.003903714,0.0004341174,0.00007852374,0.001704546,0.001944216,0.2735863,0.02971416,0.3971451,0.01021398,0.2805143],"study_design_scores_gemma":[0.0001683366,0.0001199484,0.0006697338,0.00009627088,0.00002292254,0.0003392847,0.0003832913,0.6443309,0.01481747,0.2392598,0.09972627,0.00006576797],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0684796,0.0004899013,0.8945575,0.003028767,0.0002426211,0.0006038841,0.0003024064,0.007239173,0.0250562],"genre_scores_gemma":[0.4686678,0.001387892,0.5115985,0.0003625802,0.00009084427,0.0003810924,0.0007461904,0.0006295628,0.01613552],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005624827,"threshold_uncertainty_score":0.0195359,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3206984308878495,"score_gpt":0.2536875736086036,"score_spread":0.06701085727924594,"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."}}