{"id":"W4385889098","doi":"10.1016/j.envsci.2023.103561","title":"A new index assessing adaptive capacity across Africa","year":2023,"lang":"en","type":"article","venue":"Environmental Science & Policy","topic":"Climate change impacts on agriculture","field":"Agricultural and Biological Sciences","cited_by":10,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université du Québec en Abitibi-Témiscamingue","funders":"Université du Québec en Abitibi-Témiscamingue","keywords":"Adaptive capacity; Index (typography); Geography; Vulnerability (computing); Poverty; Adaptive strategies; Range (aeronautics); Scale (ratio); Precipitation; Environmental resource management; Climate change; Climatology; Development economics; Economic growth; Environmental science; Ecology; Economics; Meteorology; Computer science; Biology; Cartography","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003894846,0.0002054207,0.0001535609,0.00003649089,0.000857904,0.0003300263,0.000561567,0.00009174712,0.0005253445],"category_scores_gemma":[0.00008677538,0.00007971285,0.0000809235,0.002312375,0.0005216182,0.0008344316,0.0004734271,0.0001748001,0.0007289674],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004313488,"about_ca_system_score_gemma":0.00003144531,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001800204,"about_ca_topic_score_gemma":0.0003468817,"domain_scores_codex":[0.9975393,0.00003506396,0.0001667858,0.0005084728,0.0007127765,0.001037623],"domain_scores_gemma":[0.9992113,0.00007340391,0.0000976172,0.0000944837,0.000007502197,0.0005157057],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.00000590732,0.00004925155,0.009931412,8.542317e-7,0.000003182814,0.000007200034,0.002551029,0.00001679221,0.8877987,0.00008551054,0.001486974,0.09806323],"study_design_scores_gemma":[0.0001118748,0.0001175967,0.9763283,0.00001127293,0.000002571494,0.00001520269,0.005761812,0.0001252623,0.006158379,0.0004958154,0.01061508,0.000256797],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9941708,0.00002141518,0.000003471305,0.002283388,0.0001002769,0.0001849801,0.000132812,0.000171598,0.002931195],"genre_scores_gemma":[0.9977242,0.00002733092,0.0000813974,0.0002952996,0.0005480376,0.000009782298,0.00002265472,0.000001581852,0.001289655],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9663969,"threshold_uncertainty_score":0.9369644,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06732762294035859,"score_gpt":0.2928842977214642,"score_spread":0.2255566747811056,"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."}}