{"id":"W3022933309","doi":"","title":"Spatial Price Differences in China: Estimates and Implications","year":2004,"lang":"en","type":"article","venue":"","topic":"Regional Economics and Spatial Analysis","field":"Economics, Econometrics and Finance","cited_by":291,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Purchasing power; Cost of living; China; Economics; Rural area; Demographic economics; Inequality; Geography; Economic growth; Macroeconomics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003239925,0.0003676781,0.0004165296,0.002015815,0.0003132414,0.0006310765,0.0008287028,0.0002534802,0.002116364],"category_scores_gemma":[0.01059558,0.0002393238,0.0007875399,0.005635436,0.0005720183,0.0008932975,0.0007966093,0.0004396141,0.0001851361],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001882601,"about_ca_system_score_gemma":0.001419208,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.2231843,"about_ca_topic_score_gemma":0.1270196,"domain_scores_codex":[0.9989246,0.0004526293,0.00007430246,0.0001774305,0.0002836662,0.00008739161],"domain_scores_gemma":[0.9946009,0.00284241,0.0007957993,0.0005654688,0.001094335,0.0001010942],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00009108914,0.00004206706,0.8914369,0.0001716039,0.0003957287,0.0002956618,0.0003987719,0.05147808,0.0002440905,0.01276169,0.00249943,0.04018484],"study_design_scores_gemma":[0.00005543193,0.00005730558,0.8427218,0.00003484342,0.0001599824,0.0001307499,0.0005753784,0.1395531,0.0006162823,0.01134126,0.004715633,0.00003823966],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9795734,0.001076853,0.01147847,0.0006071824,0.00002870795,0.00005229873,0.003610732,0.0001030193,0.003469376],"genre_scores_gemma":[0.9924842,0.0004061116,0.004494856,0.00002797007,0.00002475653,0.00002621882,0.001999996,0.000007908723,0.0005281011],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2231843,"threshold_uncertainty_score":0.4437705,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02369198851759267,"score_gpt":0.2111213210644555,"score_spread":0.1874293325468628,"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."}}