{"id":"W4387822211","doi":"10.3390/jrfm16100454","title":"Deciphering DeFi: A Comprehensive Analysis and Visualization of Risks in Decentralized Finance","year":2023,"lang":"en","type":"article","venue":"Journal of risk and financial management","topic":"Blockchain Technology Applications and Security","field":"Computer Science","cited_by":38,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; National Science Foundation","keywords":"Risk analysis (engineering); Transparency (behavior); Corporate governance; Risk management; Novelty; Computer science; Principal (computer security); Order (exchange); Finance; Business; Management science; Computer security; Engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003459801,0.0004993223,0.0003274366,0.007854377,0.0008129536,0.005219296,0.000515556,0.00110307,0.004715056],"category_scores_gemma":[0.01366646,0.0002373103,0.0004509399,0.004098142,0.001156345,0.00737904,0.002780674,0.001051238,0.0005251119],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001262745,"about_ca_system_score_gemma":0.001566794,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003129844,"about_ca_topic_score_gemma":0.003979434,"domain_scores_codex":[0.9986587,0.00054046,0.0001187396,0.0001023197,0.0004741149,0.0001056251],"domain_scores_gemma":[0.9915138,0.005651255,0.001177844,0.0005594153,0.0008500254,0.0002476172],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.0003715309,0.0001073443,0.06201207,0.001978638,0.0001638484,0.001712978,0.04696635,0.02545561,0.009454004,0.4694466,0.0242398,0.3580913],"study_design_scores_gemma":[0.00005386063,0.0001763093,0.06853981,0.002590639,0.0001592591,0.002231576,0.04224318,0.1386314,0.007153003,0.4617924,0.2761798,0.0002488071],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4076818,0.007652027,0.4673901,0.009825937,0.0002273963,0.0004582696,0.005613164,0.004130493,0.09702083],"genre_scores_gemma":[0.8684081,0.00283422,0.1218913,0.0002228745,0.00007360762,0.0001682872,0.001604391,0.0002394232,0.004557737],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007854377,"threshold_uncertainty_score":0.01829737,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01536224490075082,"score_gpt":0.2770736856917905,"score_spread":0.2617114407910397,"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."}}