{"id":"W4415766123","doi":"10.1016/j.crm.2025.100760","title":"Exploring water-energy-food nexus connections between climate action and regional development in the East African community","year":2025,"lang":"en","type":"article","venue":"Climate Risk Management","topic":"Water-Energy-Food Nexus Studies","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"United Nations University Institute for Water, Environment, and Health","funders":"HORIZON EUROPE Framework Programme; Water Research Commission; European Commission","keywords":"Nexus (standard); Interdependence; Climate change; Sustainable development; Corporate governance; Resource (disambiguation); Sustainability; Action (physics); Political economy of climate change","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":[0.008263165,0.0003094058,0.000314584,0.001962088,0.008443399,0.005312711,0.0009162509,0.001140199,0.003890031],"category_scores_gemma":[0.009106367,0.0003637211,0.0002109711,0.002493325,0.01062291,0.00662257,0.007757541,0.001822156,0.0001269843],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.008189285,"about_ca_system_score_gemma":0.009067188,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0235922,"about_ca_topic_score_gemma":0.05589422,"domain_scores_codex":[0.9939544,0.004639058,0.0001197827,0.0002110785,0.0002823985,0.0007933344],"domain_scores_gemma":[0.9936566,0.004521112,0.0007456973,0.0001421171,0.0003809841,0.0005535641],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"observational","study_design_scores_codex":[0.00001513547,0.00002714172,0.008510751,0.000223039,0.00000865802,0.001379643,0.9477287,0.0001733063,0.0006232078,0.03227048,0.0005537562,0.008486286],"study_design_scores_gemma":[0.00000193081,0.000009897212,0.005675864,0.0002046593,0.000005155764,0.0001365927,0.9811006,0.0001198555,0.0001200718,0.002429425,0.01018741,0.000008609169],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9652981,0.001985108,0.001727494,0.007729906,0.00003871008,0.00009289759,0.00005697523,0.000006251775,0.02306462],"genre_scores_gemma":[0.998035,0.0006399471,0.0004724818,0.0001870553,0.000004797507,0.00004172917,0.000008024709,0.00000355245,0.0006073264],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0235922,"threshold_uncertainty_score":0.05941772,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1187812738436225,"score_gpt":0.2555410968197139,"score_spread":0.1367598229760913,"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."}}