{"id":"W2856654253","doi":"10.54648/gtcj2018027","title":"The Unreliability of Merchandise Trade Statistics","year":2018,"lang":"en","type":"article","venue":"Global Trade and Customs Journal","topic":"Global trade and economics","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"China; International trade; Official statistics; Economics; International economics; World trade; Business; Statistics; Political science; Law","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00070795,0.0001553411,0.0003304291,0.00003417924,0.0003990752,0.0001313402,0.000288226,0.00009945894,0.0000901508],"category_scores_gemma":[0.00009210792,0.0001291239,0.0001139349,0.0001523979,0.0004908702,0.0001734959,0.00003760714,0.0002046212,0.00006263767],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001001503,"about_ca_system_score_gemma":0.00003737872,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005536626,"about_ca_topic_score_gemma":0.00004862537,"domain_scores_codex":[0.9985424,0.00002663673,0.0007603851,0.0002293648,0.00005360068,0.0003876487],"domain_scores_gemma":[0.9991099,0.00005900385,0.0003797983,0.0002231743,0.00001967908,0.0002084668],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001571456,0.0001606143,0.08607628,0.00003323856,0.0002020736,0.00001026544,0.0004939208,0.00001639864,0.00001754615,0.8662375,0.02353125,0.02306382],"study_design_scores_gemma":[0.001192932,0.0004616809,0.2636288,0.0000204156,0.00003542254,0.0002843647,0.000438962,0.0008386014,0.00007205205,0.4080804,0.3246161,0.0003302799],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9270112,0.01259085,0.007401302,0.01047429,0.003209594,0.000350538,0.002573446,0.0000445045,0.03634428],"genre_scores_gemma":[0.9966252,0.001825792,0.0008929645,0.0002831192,0.0003154147,0.000001837875,0.000003154373,0.000008966348,0.00004349732],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.458157,"threshold_uncertainty_score":0.5265521,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04090929531177531,"score_gpt":0.2359491890343322,"score_spread":0.1950398937225569,"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."}}