{"id":"W2028852071","doi":"10.5430/rwe.v1n1p10","title":"Functionary Mechanism between Demographic Structure and Economic Growth in China Based on Cointegrating Methods","year":2010,"lang":"en","type":"article","venue":"Research in World Economy","topic":"Economic Growth and Productivity","field":"Economics, Econometrics and Finance","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Science Foundation","keywords":"Cointegration; Economics; China; Error correction model; Per capita; Birth rate; Demographic transition; Wage; Population; Demographic economics; Labour economics; Econometrics; Fertility; Demography; 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":[0.002666072,0.0004203515,0.0005997476,0.001723472,0.0005055406,0.001124201,0.0006486223,0.0006106982,0.002171603],"category_scores_gemma":[0.008986478,0.0002396828,0.001031585,0.001677224,0.0008105093,0.001530677,0.0007541602,0.0005729945,0.0001390072],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009717423,"about_ca_system_score_gemma":0.001793403,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02152277,"about_ca_topic_score_gemma":0.01086572,"domain_scores_codex":[0.9987674,0.0006250361,0.00007282183,0.0002734083,0.0000990749,0.0001622861],"domain_scores_gemma":[0.9969982,0.001802031,0.0005695752,0.0001819795,0.0003566989,0.0000915885],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001540524,0.0001287774,0.4435543,0.0002212327,0.0006666129,0.001092705,0.001786016,0.2528274,0.001808338,0.1917432,0.001938203,0.1040793],"study_design_scores_gemma":[0.00002407469,0.00006126699,0.06412966,0.00003591,0.0001528688,0.00008851353,0.0002611782,0.9047943,0.0004935283,0.02862538,0.001300486,0.00003276816],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7685199,0.000974126,0.2249784,0.001130182,0.00007977361,0.0001000621,0.0003249945,0.0002146952,0.003677781],"genre_scores_gemma":[0.9924154,0.0003827351,0.005605823,0.00003262566,0.00002159071,0.00005448816,0.000177688,0.00001137173,0.001298154],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02152277,"threshold_uncertainty_score":0.04279494,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05412082470434268,"score_gpt":0.3197204099353617,"score_spread":0.265599585231019,"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."}}