{"id":"W4390099264","doi":"10.1007/s10661-023-12229-y","title":"A regional stocktake of maize yield vulnerability to droughts in the Horn of Africa","year":2023,"lang":"en","type":"article","venue":"Environmental Monitoring and Assessment","topic":"Climate change impacts on agriculture","field":"Agricultural and Biological Sciences","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université du Québec en Abitibi-Témiscamingue","funders":"","keywords":"Vulnerability (computing); Adaptive capacity; Index (typography); Geography; Vulnerability index; Composite index; Yield (engineering); Agriculture; Climate change; Vulnerability assessment; Environmental science; Ecology; Composite indicator; Mathematics; Biology; Econometrics; Psychological intervention","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":[0.0002624649,0.0001990146,0.0001359334,0.0006369608,0.0002781595,0.0002951915,0.0002032911,0.0001638748,0.0009061694],"category_scores_gemma":[0.0005959538,0.0001141557,0.0001848256,0.0007703853,0.0001445539,0.000310085,0.0003346003,0.0001396574,0.0001207196],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007121589,"about_ca_system_score_gemma":0.0003141216,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0644633,"about_ca_topic_score_gemma":0.08196325,"domain_scores_codex":[0.9999189,0.00002209944,0.000004910745,0.00001926323,0.000009224813,0.00002558382],"domain_scores_gemma":[0.9996992,0.00005573319,0.00011115,0.00002182191,0.00006716003,0.00004485849],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005318781,0.0000524007,0.9636918,0.00007208952,0.0001853812,0.0009275747,0.002455504,0.002320567,0.01502107,0.0003576003,0.0003691189,0.01401508],"study_design_scores_gemma":[0.000004213061,0.00006051901,0.9968561,0.000005137493,0.00002535783,0.0001636281,0.001157384,0.0008379967,0.0005887626,0.00002840365,0.0002676879,0.000004896431],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9992921,0.00003081141,0.00004279823,0.00001789227,4.714072e-7,0.000002461405,0.0003369172,0.000001848482,0.0002745306],"genre_scores_gemma":[0.9996369,0.00002885804,0.00007373087,0.00000213399,5.627178e-7,0.000002239476,0.0001152621,6.841476e-7,0.0001395664],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0644633,"threshold_uncertainty_score":0.1281762,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08234146143931445,"score_gpt":0.294163847773494,"score_spread":0.2118223863341795,"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."}}