{"id":"W2295566522","doi":"","title":"Productivity differences by export destination","year":2016,"lang":"en","type":"preprint","venue":"RePEc: Research Papers in Economics","topic":"Global trade and economics","field":"Economics, Econometrics and Finance","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Productivity; Total factor productivity; China; International trade; Business; Market share; International economics; Economics; Economic geography; Geography; Economic growth","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.001502177,0.0003242531,0.0005829997,0.002416737,0.0002206695,0.001787208,0.0005066062,0.0003344973,0.01580517],"category_scores_gemma":[0.009000166,0.000145022,0.001151519,0.003060114,0.0003458271,0.0009375361,0.001423022,0.0007464766,0.002931364],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004150955,"about_ca_system_score_gemma":0.0002499505,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002847722,"about_ca_topic_score_gemma":0.001184918,"domain_scores_codex":[0.9988772,0.0002078878,0.00008415071,0.0003166744,0.0002211385,0.0002928894],"domain_scores_gemma":[0.9912419,0.004023178,0.00216279,0.0009369716,0.0008664943,0.0007685893],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003692228,0.0001330482,0.9680247,0.0001553177,0.0006009979,0.0003103027,0.0007926124,0.001861443,0.001266263,0.002701345,0.002443705,0.02134096],"study_design_scores_gemma":[0.00002725649,0.0001828237,0.9893954,0.00002756963,0.00008350673,0.000199174,0.001096045,0.001265693,0.0005031721,0.00156085,0.005643757,0.00001474191],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9823428,0.0004878261,0.001696122,0.0001871412,0.0000290029,0.00002468341,0.00663738,0.00005128065,0.008543842],"genre_scores_gemma":[0.9893588,0.0001559683,0.0002851056,0.00002740298,0.00002121959,0.00001559495,0.006259379,0.00002206762,0.003854433],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01580517,"threshold_uncertainty_score":0.05287349,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09521296269685653,"score_gpt":0.2853211965359856,"score_spread":0.1901082338391291,"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."}}