{"id":"W7038418012","doi":"","title":"Growing Apart: China and India\\nat the Kigali Amendment to\\nthe Montreal Protocol","year":2023,"lang":"en","type":"article","venue":"Project Muse (Johns Hopkins University)","topic":"Human Rights and Development","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"China; Negotiation; Montreal Protocol; Politics; Divergence (linguistics); Position (finance)","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":[0.006155652,0.0003438695,0.0002663227,0.000815333,0.01185771,0.007838326,0.00147035,0.003718989,0.006529693],"category_scores_gemma":[0.007710985,0.0002993582,0.0003471048,0.002000359,0.009200272,0.003055881,0.00605433,0.006235388,0.0004295263],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02179001,"about_ca_system_score_gemma":0.056773,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.3418682,"about_ca_topic_score_gemma":0.5055887,"domain_scores_codex":[0.9924981,0.002252723,0.0001981796,0.0006204591,0.001773711,0.002656823],"domain_scores_gemma":[0.9965707,0.001455423,0.0002623806,0.0003132911,0.0006053548,0.0007927006],"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":[0.00004822088,0.00002913931,0.003379758,0.00004287402,0.000009588235,0.0004977972,0.01856739,0.0002795468,0.000627566,0.937986,0.02524634,0.01328562],"study_design_scores_gemma":[0.00007342029,0.0001048081,0.02877765,0.0003511879,0.00004220815,0.0002049701,0.02684029,0.0007238932,0.001669932,0.05446248,0.8865238,0.0002253469],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.1442159,0.001989756,0.003535654,0.1003973,0.0007175561,0.0004357302,0.0002449125,0.00006969224,0.7483935],"genre_scores_gemma":[0.7905724,0.0009136557,0.002142173,0.03324102,0.0001495524,0.0004337693,0.0002213978,0.00004941036,0.1722767],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.3418682,"threshold_uncertainty_score":0.6797566,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02511031500923963,"score_gpt":0.2729749083235294,"score_spread":0.2478645933142898,"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."}}