{"id":"W2913147232","doi":"10.1257/aeri.20180358","title":"Estimating US Consumer Gains from Chinese Imports","year":2019,"lang":"en","type":"article","venue":"American Economic Review Insights","topic":"Global trade and economics","field":"Economics, Econometrics and Finance","cited_by":39,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"Social Sciences and Humanities Research Council of Canada; Booth School of Business, University of Chicago; University of Chicago","keywords":"Economics; Inflation (cosmology); Benchmarking; Price index; Consumer price index (South Africa); Point (geometry); Percentage point; Construct (python library); Index (typography); Monetary economics; International economics; Econometrics; Monetary policy","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0009488282,0.0003469067,0.0002582537,0.001712698,0.0001797971,0.0007366862,0.000276085,0.000359748,0.004053298],"category_scores_gemma":[0.002837523,0.0001855549,0.0009206763,0.002001947,0.0003549869,0.0008073466,0.0007457638,0.0005038492,0.0005658997],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002122207,"about_ca_system_score_gemma":0.0008030609,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.07972964,"about_ca_topic_score_gemma":0.0441108,"domain_scores_codex":[0.9997595,0.00002906714,0.00001992647,0.00006108539,0.00007351894,0.00005692552],"domain_scores_gemma":[0.9987123,0.0003002554,0.0005183857,0.00008213662,0.0002943974,0.00009247665],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002459573,0.00009862836,0.9525601,0.0001137557,0.0002547523,0.0002926484,0.0004044229,0.01648253,0.0004622881,0.003480336,0.007040989,0.01856344],"study_design_scores_gemma":[0.00002136748,0.00006221484,0.9728853,0.0000233279,0.0001323883,0.0000564572,0.000479737,0.01950026,0.0004330662,0.0007079614,0.005675925,0.00002206428],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.986075,0.0003407018,0.0009311249,0.0003081906,0.00001949917,0.00004241718,0.00712838,0.00003521404,0.005119345],"genre_scores_gemma":[0.9848645,0.0002706723,0.0004078452,0.00006774175,0.00002663406,0.00004731708,0.01150673,0.000008565838,0.002799936],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07972964,"threshold_uncertainty_score":0.1585311,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0328333336147859,"score_gpt":0.2507266853615234,"score_spread":0.2178933517467375,"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."}}