{"id":"W4391012202","doi":"10.3390/jrfm17010038","title":"Decentralized Data and Artificial Intelligence Orchestration for Transparent and Efficient Small and Medium-Sized Enterprises Trade Financing","year":2024,"lang":"en","type":"article","venue":"Journal of risk and financial management","topic":"FinTech, Crowdfunding, Digital Finance","field":"Business, Management and Accounting","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"University of Washington; TD Bank","keywords":"Trade finance; Orchestration; Transparency (behavior); Credibility; Predictability; Supply chain; Cash flow; Business; Finance; Computer science; Economics; Marketing; Public finance; Computer security","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.0008567275,0.0002238481,0.0003330994,0.000312096,0.0002057986,0.0007180706,0.0001904645,0.00006709007,0.000002994775],"category_scores_gemma":[0.0002381734,0.0001936116,0.00005444928,0.0002401497,0.0001353495,0.0006927628,0.0001972203,0.0001856799,7.90321e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002542315,"about_ca_system_score_gemma":0.00002930967,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003023674,"about_ca_topic_score_gemma":0.0001059401,"domain_scores_codex":[0.9985114,0.00001163082,0.0006108268,0.0004001575,0.000197445,0.0002685838],"domain_scores_gemma":[0.9993733,0.000140625,0.0002767997,0.000133141,0.00004031987,0.00003583022],"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":[0.0005895673,0.0001200059,0.002816915,0.001587713,0.00005136046,0.00009105356,0.0005373823,0.00009995409,0.000158051,0.04157667,0.0004651009,0.9519062],"study_design_scores_gemma":[0.004536632,0.0007875405,0.2524398,0.006809736,0.002873595,0.0002121802,0.003008503,0.1487827,0.001067386,0.1484153,0.4289522,0.002114408],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5613195,0.007088321,0.4290966,0.001007462,0.0007193609,0.0005798092,0.00005302817,0.00003769179,0.00009820781],"genre_scores_gemma":[0.9897618,0.006564518,0.003129364,0.0001103403,0.0003814454,0.00001052597,0.0000128858,0.00002038755,0.00000875843],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9497918,"threshold_uncertainty_score":0.7895254,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04628653285837584,"score_gpt":0.2652723202974045,"score_spread":0.2189857874390287,"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."}}