{"id":"W2054289468","doi":"10.1080/17565529.2013.812954","title":"Institutional perceptions, adaptive capacity and climate change response in a post-conflict country: a case study from Central African Republic","year":2013,"lang":"en","type":"article","venue":"Climate and Development","topic":"Climate change impacts on agriculture","field":"Agricultural and Biological Sciences","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph; University of Prince Edward Island","funders":"Department for International Development; Social Sciences and Humanities Research Council of Canada; International Development Research Centre; Ministerio del Ambiente, Agua y Transición Ecológica","keywords":"Adaptive capacity; Climate change; Vulnerability (computing); Subsistence agriculture; Civil Conflict; Capacity building; Agriculture; Environmental resource management; Geography; Political science; Deforestation (computer science); Environmental planning; Economic growth; Economics; Ecology; Spanish Civil War","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001579158,0.0003244838,0.0003301222,0.00146994,0.01004761,0.00268298,0.000809128,0.001229565,0.002379959],"category_scores_gemma":[0.002379821,0.0003264971,0.000270898,0.002190178,0.003521129,0.001494564,0.002374047,0.001979369,0.0001248323],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00536206,"about_ca_system_score_gemma":0.003526105,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.07111659,"about_ca_topic_score_gemma":0.1353113,"domain_scores_codex":[0.9989592,0.0005019095,0.00002201234,0.00003872928,0.00006366772,0.0004144291],"domain_scores_gemma":[0.9984169,0.0007786329,0.000272778,0.000055034,0.000151528,0.0003250617],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.0001580673,0.001153227,0.1956435,0.0002126068,0.00003882181,0.0327726,0.7472932,0.000535302,0.001339415,0.005956435,0.001498776,0.01339795],"study_design_scores_gemma":[0.000006540816,0.00009449776,0.04230211,0.00009079254,0.00001129363,0.0009800292,0.9532408,0.0002319811,0.0001462285,0.0001670166,0.00271835,0.00001045166],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9989752,0.00005137322,0.00002248859,0.0001786453,0.000002103295,0.00001051672,0.0000101476,3.7591e-7,0.0007491794],"genre_scores_gemma":[0.9993964,0.0001303712,0.00007063913,0.00007507636,0.000001541832,0.00001366617,0.00001026493,8.838046e-7,0.0003010691],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07111659,"threshold_uncertainty_score":0.1414053,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07361988696674614,"score_gpt":0.2520470716295851,"score_spread":0.178427184662839,"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."}}