{"id":"W3121999802","doi":"10.1287/mnsc.2016.2628","title":"The effect of discretion on procurement performance","year":2018,"lang":"en","type":"article","venue":"Cineca Institutional Research Information System (Tor Vergata University)","topic":"Auction Theory and Applications","field":"Decision Sciences","cited_by":180,"is_retracted":false,"has_abstract":true,"ca_institutions":"HEC Montréal","funders":"","keywords":"Discretion; Regression discontinuity design; Procurement; Common value auction; Value (mathematics); Microeconomics; Judicial discretion; Language change; Business; Economics; Public economics; Computer science; Marketing; Political science; Law","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":[0.0154381,0.0003074481,0.0009484383,0.001794073,0.0005620798,0.002253519,0.001718674,0.00133651,0.006515307],"category_scores_gemma":[0.07176088,0.0003067197,0.001083491,0.002392669,0.001191607,0.000895369,0.001444933,0.002091984,0.0008685307],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001199045,"about_ca_system_score_gemma":0.0007663713,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008884193,"about_ca_topic_score_gemma":0.00600616,"domain_scores_codex":[0.9867811,0.007402114,0.0009279745,0.001936106,0.001233538,0.001719197],"domain_scores_gemma":[0.8461012,0.09564814,0.04088726,0.01151646,0.002681016,0.003165897],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001383555,0.000621594,0.9772807,0.00006695358,0.0004571469,0.0001728379,0.0005487403,0.005829935,0.0004516697,0.002097036,0.0005940255,0.01049582],"study_design_scores_gemma":[0.0001138359,0.0007879713,0.9778586,0.0000325469,0.000265138,0.0001109836,0.0005960068,0.01676934,0.0005388577,0.001675281,0.001210116,0.00004125629],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9936494,0.0002434958,0.002924853,0.0002221571,0.00001010724,0.0000515884,0.0008073293,0.0000368441,0.002054143],"genre_scores_gemma":[0.9981002,0.00003149918,0.0005024524,0.00002102588,0.0000134501,0.00003557003,0.0005287603,0.000008231907,0.000758769],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0154381,"threshold_uncertainty_score":0.08164543,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1082474948908702,"score_gpt":0.3798741685021537,"score_spread":0.2716266736112835,"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."}}