{"id":"W2949578283","doi":"10.5539/cis.v12n4p1","title":"Building High-Quality Auction Fraud Dataset","year":2019,"lang":"en","type":"article","venue":"Computer and Information Science","topic":"Auction Theory and Applications","field":"Decision Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Regina","funders":"","keywords":"Unavailability; USable; Bidding; Common value auction; Quality (philosophy); Safeguard; Paillier cryptosystem","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002591693,0.001127226,0.0007858977,0.004235274,0.001191936,0.001454159,0.002778069,0.002118057,0.00223854],"category_scores_gemma":[0.007102862,0.0004475044,0.001377024,0.00370286,0.0007061344,0.001620779,0.001642885,0.002162241,0.002763473],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001426054,"about_ca_system_score_gemma":0.001920159,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01411202,"about_ca_topic_score_gemma":0.02063803,"domain_scores_codex":[0.9968562,0.0004550319,0.0004657532,0.0006226341,0.001203792,0.0003965558],"domain_scores_gemma":[0.9958325,0.0005375121,0.0004395826,0.001192727,0.00160693,0.0003908444],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00110625,0.004396139,0.1098169,0.001312874,0.0004930396,0.002934072,0.0006573463,0.04043411,0.01189661,0.008961275,0.6228108,0.1951806],"study_design_scores_gemma":[0.0009634637,0.000987144,0.1984281,0.0003582453,0.000195739,0.003541628,0.001405443,0.3192138,0.0299428,0.009874707,0.4347892,0.0002996613],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"dataset","genre_scores_codex":[0.5139951,0.00212185,0.04124344,0.002384145,0.0008119717,0.002469126,0.4135743,0.009979444,0.01342074],"genre_scores_gemma":[0.1864683,0.0004757339,0.0746273,0.000536169,0.0001319937,0.001009041,0.7317343,0.000413158,0.004603923],"genre_candidate":"dataset","genre_consensus":null,"teacher_disagreement_score":0.01411202,"threshold_uncertainty_score":0.02805978,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06028232116417714,"score_gpt":0.4042983776417935,"score_spread":0.3440160564776164,"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."}}