{"id":"W3123018117","doi":"","title":"Trade, migration and productivity: A quantitative analysis of China","year":2015,"lang":"en","type":"preprint","venue":"","topic":"Global trade and economics","field":"Economics, Econometrics and Finance","cited_by":59,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Productivity; Economics; General equilibrium theory; China; International economics; International trade; Labour economics; Macroeconomics; Geography","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":[0.0005849294,0.000191975,0.0009886234,0.0006084441,0.0000236355,0.00006108714,0.0001502404,0.0001927611,0.00007061367],"category_scores_gemma":[0.00009864476,0.0002211247,0.0002149268,0.0003660308,0.00007095407,0.0001560204,0.0001442762,0.0001864599,0.00001830065],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000763143,"about_ca_system_score_gemma":0.00003097958,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002639511,"about_ca_topic_score_gemma":0.001180721,"domain_scores_codex":[0.9985358,0.00001489781,0.0006677209,0.0006051173,0.00002459608,0.0001518423],"domain_scores_gemma":[0.9988541,0.00002133361,0.0006308961,0.0003966679,0.00002318497,0.00007379676],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.00005355045,0.0002845081,0.2950743,0.0002323014,0.004654336,0.000001335519,0.004928438,0.01320433,0.00001112265,0.6789566,0.001918697,0.0006805431],"study_design_scores_gemma":[0.0003740609,0.0001441142,0.6422442,0.00002082843,0.0006211721,0.000001284948,0.0003710495,0.1351436,0.00005658745,0.2144634,0.005916818,0.0006429474],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9713898,0.002805571,0.001544742,0.001584116,0.0002585171,0.0002539896,0.0009029102,0.00002385763,0.02123649],"genre_scores_gemma":[0.9964804,0.0005616698,0.002441443,0.00003455931,0.0000336957,0.0000152811,0.0001652765,0.00001276533,0.0002548912],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4644932,"threshold_uncertainty_score":0.9017202,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1097171673161899,"score_gpt":0.2592680147004539,"score_spread":0.1495508473842639,"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."}}