{"id":"W4289711392","doi":"10.3390/jrfm15080341","title":"Promotion Pressures of Local Leaders and Real Estate Investments: China and Leader Heterogeneity","year":2022,"lang":"en","type":"article","venue":"Journal of risk and financial management","topic":"Local Government Finance and Decentralization","field":"Social Sciences","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Natural Science Foundation of China","keywords":"Real estate; Promotion (chess); Incentive; Investment (military); China; Business; Panel data; Local Development; Capitalization rate; Economics; Finance; Real estate investment trust; Market economy; Political science; Sociology; Regional science","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":[0.001020094,0.0001338022,0.0002444616,0.0007625351,0.0007009339,0.0007741643,0.0002859931,0.0002112509,0.002550454],"category_scores_gemma":[0.002373886,0.0001049273,0.0002332822,0.001090413,0.0007017316,0.000505738,0.0007341485,0.0003102065,0.0001612582],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007503898,"about_ca_system_score_gemma":0.00103269,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02550063,"about_ca_topic_score_gemma":0.04708311,"domain_scores_codex":[0.9993467,0.0001300551,0.00004030438,0.0001293708,0.0001340932,0.0002195358],"domain_scores_gemma":[0.9963797,0.0007274088,0.001453824,0.0002471134,0.0003076215,0.0008843666],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002605314,0.00002457743,0.9949507,0.000007737814,0.00003013439,0.000079515,0.000934936,0.0002296502,0.0001300795,0.000324984,0.0001639509,0.003097821],"study_design_scores_gemma":[0.000004152083,0.00002186416,0.997529,0.000004528651,0.00001466495,0.00001536869,0.001155533,0.0007508412,0.0000574972,0.0001530534,0.0002888059,0.00000471457],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9991522,0.00005319346,0.00007483303,0.00007184649,0.000002171745,0.000002901447,0.00003466931,0.000001634915,0.0006066539],"genre_scores_gemma":[0.9997862,0.00001639675,0.000009699323,0.000004881449,0.000002195982,0.000001167143,0.00002735685,2.406728e-7,0.0001519415],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02550063,"threshold_uncertainty_score":0.05070442,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0153587041924093,"score_gpt":0.26117524815721,"score_spread":0.2458165439648008,"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."}}