{"id":"W2013485523","doi":"10.1111/1540-5982.00143","title":"Aggregation bias, compositional change, and the border effect","year":2002,"lang":"fr","type":"article","venue":"Canadian Journal of Economics/Revue canadienne d économique","topic":"Global trade and economics","field":"Economics, Econometrics and Finance","cited_by":28,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Commodity; Economics; Aggregate (composite); Econometrics; Border effect; Aggregate data; Monetary economics; International economics; International trade; Statistics; Mathematics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.02119106,0.0005549369,0.0008559378,0.00243198,0.001185808,0.002664008,0.001121645,0.00144957,0.008632303],"category_scores_gemma":[0.08493157,0.0003633332,0.002678181,0.004483227,0.002864538,0.002266361,0.002896314,0.001699921,0.001289717],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001498612,"about_ca_system_score_gemma":0.0009727079,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01813408,"about_ca_topic_score_gemma":0.01505863,"domain_scores_codex":[0.9806234,0.01067333,0.001306185,0.002953632,0.003426897,0.001016503],"domain_scores_gemma":[0.8816771,0.07438897,0.01903468,0.0188906,0.005135424,0.0008733256],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0007821922,0.0001156715,0.8522626,0.000417312,0.002227268,0.0004662387,0.001880749,0.008711454,0.002272396,0.0275094,0.005319932,0.09803479],"study_design_scores_gemma":[0.00009222112,0.0002596907,0.931886,0.0002510962,0.001487186,0.0003646025,0.001489329,0.01440902,0.004483898,0.02688981,0.01832247,0.0000647006],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.849636,0.007176731,0.09462901,0.004259565,0.0005736286,0.0003976188,0.002287676,0.0004034746,0.04063626],"genre_scores_gemma":[0.9846851,0.000902698,0.008616139,0.0006093956,0.0001742657,0.00007629465,0.001230186,0.00006481846,0.003641042],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02119106,"threshold_uncertainty_score":0.1120704,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2734819657568709,"score_gpt":0.1842607079533785,"score_spread":0.08922125780349244,"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."}}