{"id":"W2289443796","doi":"10.14288/1.0077716","title":"Standby letters of credit and fraud","year":2010,"lang":"en","type":"article","venue":"cIRcle (University of British Columbia)","topic":"Law, logistics, and international trade","field":"Business, Management and Accounting","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Business; Computer security; Computer science; Actuarial science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0000999267,0.00002616555,0.0001311467,0.00004267902,0.00009196053,0.00009445989,0.000191565,0.00004815141,0.0002793717],"category_scores_gemma":[0.00004884818,0.00008639172,0.0000473298,0.00008852697,0.0004125483,0.0005163774,0.00009938505,0.0000880528,0.00001004618],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000006846755,"about_ca_system_score_gemma":0.000009596847,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.05757449,"about_ca_topic_score_gemma":0.0944235,"domain_scores_codex":[0.9994866,0.00000282845,0.00008226355,0.0001569518,0.0001680866,0.0001032709],"domain_scores_gemma":[0.9995978,0.00002187721,0.0001233335,0.0001039557,0.0001397613,0.00001329418],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0000573144,0.0004510753,0.5069355,0.0009028068,0.0002074694,0.000225258,0.0002076607,0.00001551308,0.02054774,0.004660429,0.1313061,0.3344832],"study_design_scores_gemma":[0.0005346608,0.000008204825,0.9891205,0.00004241342,0.00002922972,0.000005036651,0.0002378216,0.0002628128,0.000001745301,0.001413688,0.008243841,0.00009997952],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9905713,0.00001973692,0.0004939985,0.0003097967,0.0003499,0.00006596174,0.00004724319,0.00002647135,0.008115616],"genre_scores_gemma":[0.9989731,0.00002096363,0.0003067868,0.0002053287,0.0002255847,8.481302e-8,0.00001331184,0.000006380373,0.0002485116],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4821851,"threshold_uncertainty_score":0.9487012,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008591124801421724,"score_gpt":0.1607636186959438,"score_spread":0.1521724938945221,"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."}}