{"id":"W2807512355","doi":"10.1007/978-3-319-92058-0_29","title":"Online Detection of Shill Bidding Fraud Based on Machine Learning Techniques","year":2018,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Imbalanced Data Classification Techniques","field":"Computer Science","cited_by":23,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Regina","funders":"","keywords":"Bidding; Computer science; Common value auction; Support vector machine; Classifier (UML); Artificial intelligence; Machine learning; Data mining; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001109794,0.0004789441,0.0005035275,0.001675867,0.0002207388,0.0002111235,0.002960977,0.0003911126,0.00002935061],"category_scores_gemma":[0.0002939943,0.0004452708,0.0001191797,0.0008736725,0.0006754406,0.0004911549,0.0007642948,0.001061101,0.00001600188],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003474032,"about_ca_system_score_gemma":0.0002555848,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000250501,"about_ca_topic_score_gemma":0.00005216673,"domain_scores_codex":[0.9964777,0.00006911786,0.0006346124,0.001376862,0.0009961644,0.0004455874],"domain_scores_gemma":[0.9967146,0.0004595733,0.0006491773,0.001679096,0.0003985874,0.00009898417],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001667762,0.00009830187,0.00005465744,0.00006579918,0.000007081714,0.00001416524,0.0001969537,0.00249705,0.01747854,0.002891516,0.00001070409,0.9766685],"study_design_scores_gemma":[0.0001112962,0.0006048513,0.00009084691,0.0005897454,0.000004612964,0.00001101253,7.927095e-8,0.6599035,0.3171592,0.01801646,0.003070269,0.0004381302],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0000647797,0.00006807796,0.9970343,0.0002844434,0.0004702829,0.0003821109,0.00002608973,0.0007185948,0.0009513475],"genre_scores_gemma":[0.2074342,0.00003742006,0.7912069,0.0008261219,0.0002931273,0.00001298655,0.00003448718,0.00004395272,0.0001108176],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9762304,"threshold_uncertainty_score":0.9997999,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01976981537329851,"score_gpt":0.2634754865622676,"score_spread":0.2437056711889691,"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."}}