{"id":"W4388304262","doi":"10.1002/joc.8293","title":"Drought variability, changes and hot spots across the African continent during the historical period (1928–2017)","year":2023,"lang":"en","type":"article","venue":"International Journal of Climatology","topic":"Hydrology and Drought Analysis","field":"Environmental Science","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"African Institute for Mathematical Sciences; International Development Research Centre","keywords":"Cru; Climatology; Precipitation; Geography; Empirical orthogonal functions; Period (music); Teleconnection; Climate change; Physical geography; Environmental science; Geology; Oceanography","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002486486,0.0001465701,0.0001654998,0.001358252,0.000277081,0.0003727587,0.00009654376,0.00009771121,0.0008712507],"category_scores_gemma":[0.0005351015,0.00006294554,0.0001404062,0.002227734,0.0002005004,0.0002918304,0.0003243335,0.0001503402,0.0001119465],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003169741,"about_ca_system_score_gemma":0.0002281758,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01357023,"about_ca_topic_score_gemma":0.02040912,"domain_scores_codex":[0.9999136,0.00001238249,0.00001109495,0.00002067681,0.00001696239,0.00002529882],"domain_scores_gemma":[0.9997348,0.00002834716,0.0001307361,0.00001427126,0.00005829254,0.0000335607],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00007712687,0.00001230542,0.9837856,0.00008003612,0.00009236628,0.0002359429,0.0008477611,0.0004744431,0.001008592,0.0001971608,0.0008796794,0.01230893],"study_design_scores_gemma":[0.000001212022,0.000006586348,0.9981307,0.00001347073,0.00001222323,0.00005920279,0.0004293569,0.0001546858,0.00007921339,0.00001820203,0.001093322,0.000001720116],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9973813,0.0003098068,0.0000467815,0.00003982136,0.000005415222,0.000002649816,0.001842122,0.000003423203,0.0003686283],"genre_scores_gemma":[0.9982933,0.0002571649,0.00006130092,0.000004520854,0.00001275018,0.000005160024,0.00124314,0.000001105372,0.0001215361],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01357023,"threshold_uncertainty_score":0.02698249,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01341898601492115,"score_gpt":0.277785678242546,"score_spread":0.2643666922276249,"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."}}