{"id":"W4285723216","doi":"10.2139/ssrn.4055451","title":"The Trade and Economic Impact of the CUSMA: Making Sense of the Alternative Estimates","year":2020,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Global trade and economics","field":"Economics, Econometrics and Finance","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Centre for International Governance Innovation; Asia Pacific Foundation of Canada","funders":"","keywords":"Economics; Sense (electronics); Engineering","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01577299,0.001282985,0.001758862,0.004624215,0.0008294556,0.007206083,0.002566034,0.002242292,0.01586307],"category_scores_gemma":[0.08377137,0.0005092582,0.001720605,0.005274392,0.003898893,0.00660927,0.002546167,0.005098374,0.0006564457],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001485681,"about_ca_system_score_gemma":0.001300538,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00937327,"about_ca_topic_score_gemma":0.009271881,"domain_scores_codex":[0.9905635,0.006063453,0.0004195511,0.0009167392,0.00162661,0.0004100954],"domain_scores_gemma":[0.8762057,0.1101633,0.00449604,0.00505758,0.003435891,0.0006415943],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00114613,0.0001532995,0.02296673,0.000701072,0.001437363,0.0009215818,0.0006656713,0.0867609,0.0006123901,0.79131,0.01058554,0.08273926],"study_design_scores_gemma":[0.0001958514,0.0002605168,0.01958538,0.0004961347,0.001384123,0.0002500274,0.001378165,0.2845249,0.001223945,0.6762066,0.01432508,0.0001692546],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3282141,0.03713223,0.4477049,0.02965737,0.004282845,0.0002116957,0.003124465,0.0004456518,0.1492269],"genre_scores_gemma":[0.963747,0.005515669,0.02194704,0.0006720845,0.001856886,0.00006963587,0.0006212968,0.000123261,0.005447151],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9985143,"threshold_uncertainty_score":0.08341652,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02973770329319339,"score_gpt":0.2330251360023894,"score_spread":0.203287432709196,"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."}}