{"id":"W1964904532","doi":"10.5539/jsd.v5n7p149","title":"Cultivated Land Area Change in Shenzhen and Its Socio-Economic Driving Forces Based on STIRPAT Model","year":2012,"lang":"en","type":"article","venue":"Journal of Sustainable Development","topic":"Regional Economic and Spatial Analysis","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Urbanization; Cultivated land; Kuznets curve; Geography; Driving factors; Population; Agricultural economics; China; Environmental protection; Natural resource economics; Economics; Economic growth; Agriculture; Demography","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":[0.000357165,0.0003744951,0.0003679195,0.001116239,0.0004525494,0.001404843,0.0008900143,0.0005774496,0.004247208],"category_scores_gemma":[0.0008280003,0.0001879595,0.001036797,0.001102597,0.0004813612,0.001073439,0.0007610516,0.0004495707,0.0004803895],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001252069,"about_ca_system_score_gemma":0.0007714329,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04282641,"about_ca_topic_score_gemma":0.02547538,"domain_scores_codex":[0.9998177,0.00004103994,0.000008331157,0.00005184324,0.00002476495,0.00005631471],"domain_scores_gemma":[0.9997169,0.0001028901,0.00005527498,0.00001492385,0.00005416055,0.00005579368],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0002393081,0.0001934435,0.2678303,0.0001278626,0.0002885096,0.002011573,0.0006748331,0.6548238,0.002056842,0.05134886,0.003945367,0.01645923],"study_design_scores_gemma":[0.00001571855,0.00005525247,0.03191636,0.00000972731,0.00006267628,0.0001438199,0.0003910378,0.9608803,0.0001202507,0.005164407,0.001217552,0.00002293418],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9740629,0.0001840688,0.01431875,0.0007879261,0.00002825233,0.00003391171,0.000710918,0.0001105251,0.009762851],"genre_scores_gemma":[0.9974522,0.0000993119,0.0003636555,0.00001494527,0.000007869651,0.00001458534,0.0002111692,0.000007419247,0.001828829],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04282641,"threshold_uncertainty_score":0.08515429,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04187407036404125,"score_gpt":0.2276229543138321,"score_spread":0.1857488839497908,"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."}}