{"id":"W4399433522","doi":"10.1080/00207543.2024.2361434","title":"Supply chain fraud prediction with machine learning and artificial intelligence","year":2024,"lang":"en","type":"article","venue":"International Journal of Production Research","topic":"Imbalanced Data Classification Techniques","field":"Computer Science","cited_by":34,"is_retracted":false,"has_abstract":true,"ca_institutions":"Royal Roads University","funders":"","keywords":"Artificial intelligence; Supply chain; Computer science; Machine learning; Engineering; Business","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":[0.007527907,0.001151884,0.001119675,0.007908526,0.0009242587,0.003564184,0.001298155,0.00162164,0.001294689],"category_scores_gemma":[0.02208315,0.0005179417,0.001070582,0.005986853,0.0009074744,0.003955171,0.001682704,0.002517266,0.0006016452],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00190544,"about_ca_system_score_gemma":0.001873857,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007867441,"about_ca_topic_score_gemma":0.005309749,"domain_scores_codex":[0.9963467,0.001867965,0.0003497545,0.0004716052,0.0006977251,0.0002663149],"domain_scores_gemma":[0.9822498,0.01230828,0.002148462,0.001136698,0.001854501,0.0003022309],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003544006,0.001336508,0.1541056,0.0003031143,0.0005402309,0.0002522068,0.0002842821,0.4305444,0.0006063733,0.008369974,0.005315307,0.3979875],"study_design_scores_gemma":[0.000009234602,0.00005241652,0.005456265,0.00005592169,0.00002049044,0.00003751205,0.00009822148,0.9827659,0.0003282519,0.01027302,0.0008899521,0.00001282178],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.442337,0.00674053,0.5279613,0.008021964,0.0004586698,0.0006157138,0.001599508,0.00171163,0.01055368],"genre_scores_gemma":[0.8931492,0.001009594,0.1029426,0.00031011,0.0002910906,0.0001470872,0.00102679,0.00002296038,0.001100586],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007908526,"threshold_uncertainty_score":0.03981185,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07692584221330417,"score_gpt":0.3965441986824003,"score_spread":0.3196183564690961,"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."}}