{"id":"W3124488014","doi":"","title":"Ai and International Trade","year":2018,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Digital Platforms and Economics","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Competition (biology); Context (archaeology); International trade; Affect (linguistics); Economics; Political science; Industrial organization; Business; Sociology; Geography","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":[0.001517189,0.0002863071,0.0003714097,0.001892988,0.002874699,0.007284318,0.0004889246,0.002244083,0.02298394],"category_scores_gemma":[0.003364724,0.00013803,0.0004547451,0.003025822,0.006460373,0.006411572,0.002910117,0.00217691,0.001493255],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003026684,"about_ca_system_score_gemma":0.001575499,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001995907,"about_ca_topic_score_gemma":0.001575694,"domain_scores_codex":[0.9987043,0.0004881858,0.00005816574,0.0002534385,0.000307541,0.0001882964],"domain_scores_gemma":[0.997543,0.001220934,0.0003674018,0.0003830414,0.0002715502,0.0002140603],"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":[0.000003792117,0.000004855801,0.0002318628,0.00001292388,0.000003848005,0.00002000268,0.0001069835,0.0003676183,0.00001922068,0.991987,0.001078123,0.006163758],"study_design_scores_gemma":[0.000003478081,0.000009006636,0.0006475177,0.0001068035,0.000003267542,0.00006869779,0.0003791275,0.0004750203,0.00003727277,0.9070792,0.09118477,0.000006013805],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.02027326,0.02286018,0.01510807,0.0296897,0.0005745873,0.00002444965,0.0001452523,0.00004634121,0.9112782],"genre_scores_gemma":[0.9105941,0.02495779,0.005172478,0.004772741,0.001489757,0.0001044395,0.0001686018,0.00005223519,0.05268788],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02298394,"threshold_uncertainty_score":0.07688892,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009011664575663611,"score_gpt":0.2093931846537932,"score_spread":0.2003815200781296,"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."}}