{"id":"W3144972453","doi":"","title":"Corruption, Government Subsidies, and Innovation: Evidence from China","year":2018,"lang":"en","type":"article","venue":"National Bureau of Economic Research","topic":"Innovation Policy and R&D","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Subsidy; Language change; Government (linguistics); China; Quarter (Canadian coin); Politics; Economics; Rent-seeking; Business; Public economics; Private sector; Economic policy; Market economy; Economic growth; Political science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001753491,0.0003187295,0.0005367602,0.002271586,0.0009977535,0.0009776689,0.0004765309,0.0005086537,0.002359512],"category_scores_gemma":[0.003711934,0.0001993657,0.0007251059,0.003738861,0.001299452,0.0005048306,0.001066254,0.0005211945,0.0002112528],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002049156,"about_ca_system_score_gemma":0.003769177,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1927441,"about_ca_topic_score_gemma":0.2283249,"domain_scores_codex":[0.9991022,0.0001926426,0.00007930706,0.0001150847,0.0002054195,0.0003053045],"domain_scores_gemma":[0.9899095,0.002138699,0.004961028,0.0004984284,0.001274929,0.001217401],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0000753943,0.0001025135,0.9913477,0.00006888338,0.0001585239,0.0002016417,0.0004775532,0.0003552306,0.0001055237,0.0004927906,0.0006277717,0.005986518],"study_design_scores_gemma":[0.00001889674,0.00003731043,0.9980459,0.0000246381,0.0001152936,0.00003345994,0.0004404202,0.0004879681,0.00007724622,0.00009224113,0.0006196026,0.000006900051],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9973046,0.0007278282,0.00005065799,0.0004422663,0.00000544539,0.000009347063,0.0002733222,0.000003465515,0.001183018],"genre_scores_gemma":[0.9987788,0.0005239688,0.00002765159,0.00007713003,0.00001166745,0.000004307284,0.0002751102,0.000001217946,0.000300164],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1927441,"threshold_uncertainty_score":0.3832445,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4211206787049164,"score_gpt":0.4691150739016577,"score_spread":0.04799439519674131,"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."}}