{"id":"W2963773692","doi":"10.1007/s42452-019-0912-7","title":"Vulnerability of crop yields to variations in growing season precipitation in Uganda","year":2019,"lang":"en","type":"article","venue":"SN Applied Sciences","topic":"Climate change impacts on agriculture","field":"Agricultural and Biological Sciences","cited_by":14,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"","keywords":"Geography; Socioeconomics; Poverty; Population; Vulnerability (computing); Census; Food security; Economic growth; Agriculture; Demography; Economics; Sociology","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":[0.0005271763,0.000192093,0.0002372196,0.0007519639,0.0006642535,0.0007171981,0.0002878225,0.0003011025,0.001269782],"category_scores_gemma":[0.002607929,0.0003117848,0.0002915938,0.0009303432,0.0004846227,0.0004684933,0.00147005,0.0004473523,0.0001964378],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000814381,"about_ca_system_score_gemma":0.000347962,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01668953,"about_ca_topic_score_gemma":0.0193518,"domain_scores_codex":[0.9996182,0.000148661,0.0000224793,0.00004534283,0.00002025379,0.0001449676],"domain_scores_gemma":[0.9988441,0.0004660204,0.0003716925,0.000068835,0.0001117392,0.0001375124],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003557488,0.00005499839,0.9850036,0.00003552792,0.0001265849,0.0007640236,0.003777795,0.002055407,0.0009992501,0.0004330772,0.0001990566,0.006194912],"study_design_scores_gemma":[0.000004224814,0.00008221024,0.9943961,0.00001454376,0.00002372535,0.0003379245,0.003142899,0.001279545,0.0001772562,0.0002194446,0.0003146612,0.000007580719],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.999658,0.00003740788,0.00002910147,0.00001742928,6.601445e-7,0.000001431574,0.00005017107,8.893862e-7,0.0002048639],"genre_scores_gemma":[0.999836,0.00003404217,0.00001425703,0.000003161527,6.094952e-7,0.000002548475,0.000024777,6.356572e-7,0.00008408171],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01668953,"threshold_uncertainty_score":0.03318477,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03680613116551292,"score_gpt":0.2749737671885644,"score_spread":0.2381676360230515,"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."}}