{"id":"W4212861275","doi":"10.5539/jas.v14n3p12","title":"The Impact of State Ownership on the Productivity of China’s Agri-food Firms","year":2022,"lang":"en","type":"article","venue":"Journal of Agricultural Science","topic":"Firm Innovation and Growth","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Total factor productivity; Productivity; Quantile regression; Quantile; Panel data; Distribution (mathematics); Business; China; State ownership; Agricultural economics; Economics; Labour economics; Econometrics; Economic growth; Finance; Emerging markets; Geography","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.0007965956,0.0001691207,0.0002255083,0.001076165,0.0003326883,0.0008790788,0.0002636206,0.0001828956,0.001823481],"category_scores_gemma":[0.003378564,0.0001128054,0.000430258,0.001757338,0.0004939535,0.0005786198,0.000676981,0.0003525814,0.0001665786],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001174544,"about_ca_system_score_gemma":0.0008589412,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05490785,"about_ca_topic_score_gemma":0.05586387,"domain_scores_codex":[0.9995313,0.00006305635,0.00003131215,0.00009118313,0.00009272219,0.0001904644],"domain_scores_gemma":[0.9962906,0.0007813305,0.001675269,0.0002542797,0.0005468533,0.0004516751],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002755411,0.00001622188,0.9943591,0.000006856439,0.00004993018,0.00007942249,0.0001313244,0.0006009481,0.0002259459,0.0002367311,0.0002245357,0.004041456],"study_design_scores_gemma":[0.000001625715,0.00001118364,0.998485,0.000002503451,0.00001644303,0.00001464101,0.0001257844,0.0009517697,0.00009889267,0.00006584657,0.0002233713,0.000002774558],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9983536,0.000173371,0.0001352592,0.0001182764,0.000003625497,0.000003025988,0.0004419425,0.000007066215,0.0007639024],"genre_scores_gemma":[0.9994127,0.00005306594,0.00001310881,0.000007129151,0.000003280039,9.978447e-7,0.0003066546,6.65984e-7,0.0002023659],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05490785,"threshold_uncertainty_score":0.1091765,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03251460262203523,"score_gpt":0.229845764520604,"score_spread":0.1973311618985688,"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."}}