{"id":"W3123415952","doi":"10.1016/s0047-2727(03)00074-4","title":"Competition and the reform of incentive schemes in the regulated sector","year":2003,"lang":"en","type":"article","venue":"Journal of Public Economics","topic":"Auction Theory and Applications","field":"Decision Sciences","cited_by":12,"is_retracted":false,"has_abstract":false,"ca_institutions":"Center for Interuniversity Research and Analysis on Organizations; Université de Montréal","funders":"","keywords":"Incentive; Adverse selection; Principal (computer security); Constraint (computer-aided design); Competition (biology); Economics; Microeconomics; Private information retrieval; Function (biology); Principal–agent problem; Participation constraint; Private sector; Industrial organization; Public economics; Computer science; Finance; Corporate governance; Mathematics","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":[],"consensus_categories":[],"category_scores_codex":[0.007245908,0.0000385015,0.0001458036,0.0001183935,0.00007919739,0.00009945112,0.0003112113,0.00002748051,0.0001189185],"category_scores_gemma":[0.0005919337,0.00001807139,0.00005830607,0.0002419534,0.0002403886,0.0003650988,0.00001781909,0.0001209038,0.00000389624],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004381558,"about_ca_system_score_gemma":0.00006441841,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003303946,"about_ca_topic_score_gemma":0.00002368839,"domain_scores_codex":[0.9988933,0.000307354,0.0005636771,0.00006339422,0.0001120184,0.00006029751],"domain_scores_gemma":[0.9982784,0.0006287075,0.0007162453,0.0001699297,0.0001816083,0.00002509065],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00002035382,0.00002458672,0.0009888775,4.804159e-7,0.000009576906,1.01447e-7,0.000436083,0.00004415952,0.00001979778,0.9968427,0.0001034925,0.00150972],"study_design_scores_gemma":[0.001403801,0.00004276238,0.01385024,0.000008025885,0.000009325487,0.00009513061,0.01845084,0.0006362351,0.0006589508,0.8822789,0.08251055,0.0000552605],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9854527,0.00009100844,0.001877735,0.006396106,0.00008888454,0.00006873663,0.000002968299,9.657047e-7,0.006020929],"genre_scores_gemma":[0.999373,0.00008487569,0.000243005,0.0001661297,0.0000324256,0.000001627851,2.902275e-7,0.000001698651,0.00009698401],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1145639,"threshold_uncertainty_score":0.2511302,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0845461713437377,"score_gpt":0.3176327060481753,"score_spread":0.2330865347044376,"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."}}