{"id":"W2525203951","doi":"","title":"The EU, China and the Paris Climate Summit","year":2015,"lang":"en","type":"article","venue":"Lirias (KU Leuven)","topic":"Environmental Policies and Emissions","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Summit; China; Political science; Climate change; Geography; Climatology; Physical geography; Geology; Law; Oceanography","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003594758,0.0007424926,0.0003234044,0.000828867,0.00432743,0.007976987,0.0008707216,0.003875277,0.01095071],"category_scores_gemma":[0.003504296,0.0002363962,0.0004674078,0.00109025,0.003524507,0.003660779,0.004748491,0.003340003,0.0009128668],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01117911,"about_ca_system_score_gemma":0.01581072,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.08296083,"about_ca_topic_score_gemma":0.1056285,"domain_scores_codex":[0.997425,0.0007142717,0.00005794991,0.0001880399,0.0004344362,0.00118041],"domain_scores_gemma":[0.9989539,0.0002399736,0.000104001,0.00007038002,0.000196199,0.0004355231],"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":[0.0002989663,0.00005299774,0.005193923,0.0002363857,0.00009557541,0.001006876,0.003315132,0.00334409,0.0004969122,0.6559095,0.2767086,0.05334101],"study_design_scores_gemma":[0.00002884106,0.00003778248,0.007918146,0.0001743204,0.00001847901,0.00005016767,0.003854024,0.0003469071,0.00049846,0.01876235,0.9682698,0.00004084239],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.07904194,0.02875733,0.001481888,0.2821226,0.005336215,0.00006432607,0.0005803669,0.0002402353,0.6023751],"genre_scores_gemma":[0.6497368,0.007426471,0.001682295,0.05062742,0.001590917,0.0001221015,0.0005391083,0.000107008,0.2881678],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.08296083,"threshold_uncertainty_score":0.1649559,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00976771094557809,"score_gpt":0.2173343432996727,"score_spread":0.2075666323540946,"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."}}