{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.006544526,0.0002745658,0.0006581927,0.003002497,0.0001941416,0.0001673988,0.0003856347,0.0002046184,0.00086139],"category_scores_gemma":[0.0002574116,0.0003299029,0.000096957,0.0006410328,0.0002137178,0.000508458,0.0001326835,0.001994547,0.0001199179],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002860143,"about_ca_system_score_gemma":0.000111107,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001693717,"about_ca_topic_score_gemma":0.003673976,"domain_scores_codex":[0.9970501,0.0002294955,0.000843061,0.001074282,0.00003541954,0.0007676331],"domain_scores_gemma":[0.9980892,0.0009244848,0.0002107957,0.0005236888,0.00002226434,0.0002295785],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00002804532,0.00003406596,0.7183658,0.00004249681,0.00001408344,0.0000031355,0.00005304932,0.00007987184,0.00002822327,0.2785655,0.00007835709,0.002707384],"study_design_scores_gemma":[0.0007727183,0.00007867075,0.3979082,0.00002418951,0.00000140162,0.000002793599,0.00002161503,0.01501601,0.0005392943,0.5818382,0.003483154,0.0003137368],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9423941,0.0001929586,0.0005129384,0.003581748,0.0005089946,0.0005904883,0.0001361983,0.00003119896,0.05205141],"genre_scores_gemma":[0.9926906,0.00002903756,0.006466195,0.0001300519,0.0003630714,0.00008490198,0.00003085499,0.00004257959,0.0001627278],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3204576,"threshold_uncertainty_score":0.9999153,"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."}}