{"id":"W4387264610","doi":"10.1017/s1355770x23000074","title":"Adaptive capacity and subsequent droughts: evidence from Ethiopia","year":2023,"lang":"en","type":"article","venue":"Environment and Development Economics","topic":"Agricultural risk and resilience","field":"Agricultural and Biological Sciences","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Université de Genève; International Development Research Centre; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; National Science Foundation","keywords":"Revenue; Factoring; Adaptive capacity; Natural resource economics; Economics; Agricultural economics; Business; Climate change; Finance; Biology; Ecology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001386698,0.0001399938,0.0001342751,0.000007176999,0.0002560263,0.00004910643,0.00009956268,0.00007676997,0.0001048726],"category_scores_gemma":[0.000008011663,0.0000553887,0.00001908968,0.00004408281,0.0001020612,0.0001845286,0.0001673506,0.0000806497,0.0001734321],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005396306,"about_ca_system_score_gemma":0.000005351049,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001402586,"about_ca_topic_score_gemma":0.0002099766,"domain_scores_codex":[0.9991635,0.00002435978,0.0001754349,0.0003580608,0.0000718455,0.0002068136],"domain_scores_gemma":[0.9996162,0.0001701123,0.00006140909,0.00003439701,0.000003446547,0.000114447],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00008408509,0.00007062909,0.6118935,0.00001237076,0.00009001901,0.00001345611,0.005185287,0.0002982162,0.03905312,0.0006224425,0.0007936877,0.3418832],"study_design_scores_gemma":[0.00007056969,0.00004306987,0.9767162,0.00002007899,0.000004399657,0.000001662823,0.0006472807,0.0001664919,0.002733886,0.0004868528,0.01890144,0.0002080841],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9986947,0.0003968753,0.000008035634,0.0005903103,0.00005806848,0.0001323926,0.00001384989,0.00003921561,0.00006653852],"genre_scores_gemma":[0.9897627,0.008651341,0.0009632052,0.00009188983,0.00007305973,0.00001807994,0.00003909206,8.035009e-7,0.0003998019],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3648227,"threshold_uncertainty_score":0.2258686,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04618413292975685,"score_gpt":0.1901897157909022,"score_spread":0.1440055828611454,"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."}}