{"id":"W3122500297","doi":"10.34989/swp-2016-15","title":"How Fast Can China Grow? The Middle Kingdom’s Prospects to 2030","year":2021,"lang":"en","type":"preprint","venue":"RePEc: Research Papers in Economics","topic":"Economic Growth and Productivity","field":"Economics, Econometrics and Finance","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Bank of Canada","funders":"Hong Kong Institute for Monetary Research","keywords":"Total factor productivity; Economics; China; Human capital; Stock (firearms); Wage; Productivity; Commodity; Production (economics); Investment (military); Chinese economy; Economy; Labour economics; Macroeconomics; Market economy; Geography","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":[0.0007213717,0.0003927579,0.0002105517,0.000467969,0.0004990724,0.001726815,0.0003479319,0.0006826223,0.003627713],"category_scores_gemma":[0.001209248,0.00009498352,0.000338262,0.0008919091,0.0005268576,0.001927734,0.0008936232,0.0006418276,0.001071254],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002405491,"about_ca_system_score_gemma":0.003071743,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06853763,"about_ca_topic_score_gemma":0.0562428,"domain_scores_codex":[0.9997838,0.00002272584,0.000008692862,0.00002556759,0.00005838704,0.0001007563],"domain_scores_gemma":[0.9995834,0.00002563338,0.00006221238,0.00002429263,0.0001609894,0.0001434222],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0008503879,0.00009865228,0.3423577,0.001066314,0.0003172216,0.0038743,0.005803408,0.01922146,0.01158947,0.1489417,0.1727104,0.293169],"study_design_scores_gemma":[0.00003954757,0.0002964411,0.5528495,0.0004548623,0.0001408043,0.0004704872,0.008683654,0.01675426,0.005320294,0.02011232,0.3947246,0.0001531777],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8157512,0.01324175,0.002556748,0.07608676,0.001180486,0.00003095247,0.007535087,0.0002430306,0.08337409],"genre_scores_gemma":[0.9840745,0.004257851,0.0006442703,0.001558219,0.0001087217,0.00001282192,0.001516381,0.00003073004,0.007796492],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06853763,"threshold_uncertainty_score":0.1362774,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06939067471816451,"score_gpt":0.2667703964637786,"score_spread":0.1973797217456141,"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."}}