{"id":"W4380576135","doi":"","title":"AN ANALYSIS ON CHINA’S ECONOMICAL GROWTH PERSPECTIVES","year":2016,"lang":"en","type":"article","venue":"DOAJ (DOAJ: Directory of Open Access Journals)","topic":"Firm Innovation and Growth","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"China; Geography; Archaeology","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":[0.0007889468,0.0003449392,0.0001394321,0.004398745,0.0006164387,0.001838572,0.0002131695,0.0001534907,0.003606426],"category_scores_gemma":[0.001076933,0.0000817931,0.0003184565,0.005056816,0.000733726,0.001682442,0.0008676018,0.0004708042,0.0002581004],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002727802,"about_ca_system_score_gemma":0.00139856,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01262856,"about_ca_topic_score_gemma":0.01035207,"domain_scores_codex":[0.9996804,0.00006690676,0.00001968937,0.00004297366,0.0001307932,0.00005918669],"domain_scores_gemma":[0.9992582,0.0001904407,0.0001204733,0.00004499939,0.0003219961,0.00006389667],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001574439,0.00005962798,0.1565937,0.0007656679,0.00008894648,0.001934184,0.01928949,0.009877251,0.003769384,0.5774159,0.01171224,0.2183362],"study_design_scores_gemma":[0.00001038259,0.0002014012,0.5432243,0.0004742469,0.00009246355,0.0007976792,0.02635934,0.01722509,0.004064354,0.05844869,0.3490174,0.00008457465],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7074502,0.006230767,0.009307561,0.004273737,0.0002128111,0.00006347071,0.001769731,0.0000676354,0.2706241],"genre_scores_gemma":[0.9828209,0.00528616,0.001766458,0.0001088634,0.0001730156,0.00002755068,0.0006365463,0.00001598333,0.009164553],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01262856,"threshold_uncertainty_score":0.02511013,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2027591331612613,"score_gpt":0.4907150117831164,"score_spread":0.2879558786218551,"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."}}