{"id":"W4241227645","doi":"10.1093/jleo/ewy020","title":"Corrigendum to: Bid Rigging and Entry Deterrence in Public Procurement: Evidence from an Investigation into Collusion and Corruption in Quebec","year":2018,"lang":"en","type":"erratum","venue":"The Journal of Law Economics and Organization","topic":"Public Procurement and Policy","field":"Business, Management and Accounting","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"HEC Montréal; Concordia University","funders":"","keywords":"Collusion; Procurement; Language change; Deterrence (psychology); Business; Deterrence theory; Computer security; Political science; Law and economics; Economics; Industrial organization; Computer science; Law; Marketing","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":[0.001035504,0.0001856799,0.0002605519,0.0004345228,0.0001887821,0.0008026668,0.0002283476,0.0001607908,0.00002464774],"category_scores_gemma":[0.0002199146,0.0001572712,0.00001046764,0.000345101,0.0000884131,0.003127357,0.0002255933,0.0002515627,0.000003479591],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001744805,"about_ca_system_score_gemma":0.0001704392,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.02093796,"about_ca_topic_score_gemma":0.1404416,"domain_scores_codex":[0.9989335,0.00004421975,0.0005321189,0.0002101593,0.0001175362,0.0001624788],"domain_scores_gemma":[0.9987904,0.00002918546,0.0007740393,0.0001207875,0.0002428375,0.00004272668],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003980315,0.000203164,0.8412393,0.0008280065,0.0001175957,0.000008814016,0.02630838,0.0001159286,0.002917138,0.02647529,0.07126978,0.03011862],"study_design_scores_gemma":[0.003706574,0.0004039399,0.6416669,0.006005914,0.000457127,0.00004290868,0.002257579,0.04199149,0.000451657,0.04183814,0.2592601,0.001917633],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9924427,0.000687195,0.0001095229,0.00382047,0.002413386,0.0002976802,0.00000198891,0.000009569917,0.0002175112],"genre_scores_gemma":[0.9913051,0.004043738,0.00009455752,0.001681986,0.002203732,0.000002596109,0.00009678028,0.0000319541,0.0005395216],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1995724,"threshold_uncertainty_score":0.9855817,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03280586195221118,"score_gpt":0.2392855559919924,"score_spread":0.2064796940397813,"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."}}