{"id":"W2388634744","doi":"","title":"Influencing Factor of Investment in China from Perspective of City Space","year":2014,"lang":"en","type":"article","venue":"Resource Development & Market","topic":"Regional Economic and Spatial Analysis","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Science North","funders":"","keywords":"Investment (military); Statistic; Economics; Gross private domestic investment; China; Capital expenditure; Capital (architecture); Fixed investment; Scale (ratio); Human capital; Monetary economics; Economic geography; Macroeconomics; Capital formation; Return on investment; Economic growth; Geography; Finance; Financial capital; Open-ended investment company; Production (economics); Statistics; Mathematics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005122983,0.0001426347,0.0005691329,0.0003077805,0.00003221676,0.00001133163,0.0002089362,0.00007392225,0.0006138862],"category_scores_gemma":[0.0001849268,0.00015688,0.000104652,0.0002066214,0.00006151545,0.00007499893,0.0000884536,0.00009559353,0.00002590296],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002991199,"about_ca_system_score_gemma":0.00004695585,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004208087,"about_ca_topic_score_gemma":0.0002738177,"domain_scores_codex":[0.998633,0.00003719205,0.0007546352,0.0003389494,0.00005627061,0.0001799801],"domain_scores_gemma":[0.9990374,0.0001074747,0.0005335613,0.0002297724,0.00002658331,0.00006520987],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00008250541,0.0001368902,0.9366929,0.00003496497,0.0002400798,9.862388e-7,0.007832353,0.0003402528,0.00007479068,0.0528687,0.0004679752,0.001227608],"study_design_scores_gemma":[0.0004320188,0.00002132257,0.958801,0.00004570237,0.000004349671,1.508715e-7,0.0004316488,0.002178119,0.0005327114,0.01286371,0.02449615,0.0001931321],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9198212,0.0002860356,0.0008496814,0.0002823186,0.0000261391,0.00009604751,0.0000362603,0.00000686816,0.07859547],"genre_scores_gemma":[0.9972306,0.00003433284,0.001809557,0.0001198953,0.00002297234,0.00000745475,0.00001105569,0.00001119554,0.0007529201],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07784254,"threshold_uncertainty_score":0.6721623,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01588508286003807,"score_gpt":0.1935730666935843,"score_spread":0.1776879838335462,"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."}}