{"id":"W2945046487","doi":"","title":"Climate change and trade agreements: friends or foes?","year":2019,"lang":"en","type":"article","venue":"Figshare","topic":"Climate Change Policy and Economics","field":"Economics, Econometrics and Finance","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"International trade; Climate change; Subsidy; Trade barrier; Free trade; Economics; Greenhouse gas; Global warming; Goods and services; International economics; Natural resource economics; Business; Economy; Market economy; Ecology","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":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00007505261,0.0001525088,0.0002927363,0.0001230577,0.0000682335,0.00009041293,0.0001588132,0.0001062698,0.2463217],"category_scores_gemma":[0.00006614355,0.0001622972,0.00006264813,0.0001014344,0.000005610658,0.0003758408,0.0001482407,0.00009373084,0.01763008],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004739812,"about_ca_system_score_gemma":0.000003773359,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002560709,"about_ca_topic_score_gemma":0.00003136136,"domain_scores_codex":[0.9989169,0.000004020431,0.0003153011,0.0003587859,0.00001674306,0.000388206],"domain_scores_gemma":[0.9993858,0.00004610607,0.0001991331,0.0002659236,0.000005483996,0.00009759411],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000443149,0.0006720459,0.209078,0.006413918,0.0004976309,0.00009048093,0.01986008,0.00001326016,0.00002753289,0.1412933,0.578625,0.0429857],"study_design_scores_gemma":[0.00115538,0.0001619434,0.05468371,0.0004701901,0.000005626912,0.00001585215,0.0002564732,0.001703965,0.00004162991,0.001761258,0.9391587,0.000585281],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.09453665,0.002573769,5.3129e-7,0.001889848,0.0004773272,0.0008193617,0.797698,0.0001209899,0.1018836],"genre_scores_gemma":[0.9524474,0.001193092,0.0001222862,0.00627952,0.0007686306,0.0005434116,0.03712206,0.000100306,0.001423268],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8579108,"threshold_uncertainty_score":0.9831348,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.263760784190587,"score_gpt":0.273876681951354,"score_spread":0.01011589776076705,"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."}}