{"id":"W4406020796","doi":"10.1186/s40066-024-00509-w","title":"The impact of precipitation, temperature, and soil moisture on wheat yield gap quantification: evidence from Morocco","year":2025,"lang":"en","type":"article","venue":"Agriculture & Food Security","topic":"Climate change impacts on agriculture","field":"Agricultural and Biological Sciences","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec en Abitibi-Témiscamingue","funders":"Fondation OCP","keywords":"Yield (engineering); Precipitation; Environmental science; Agronomy; Moisture; Yield gap; Water content; Winter wheat; Soil science; Crop yield; Geography; Geology; Biology; Materials science; Meteorology","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":[0.00140027,0.0003433977,0.0002997883,0.0008524586,0.0004717222,0.000592374,0.0003840765,0.0002524321,0.0005376796],"category_scores_gemma":[0.002501725,0.0001171541,0.0003948413,0.001101306,0.0004853196,0.0003982666,0.0006394205,0.0002586056,0.0001139184],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001134704,"about_ca_system_score_gemma":0.0006391293,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.09786892,"about_ca_topic_score_gemma":0.09549321,"domain_scores_codex":[0.9994459,0.0002036885,0.00003666258,0.0001084888,0.00008049657,0.0001247391],"domain_scores_gemma":[0.9979928,0.0007064942,0.000566852,0.0001703801,0.0004422165,0.0001212667],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001672766,0.00004019174,0.9752229,0.0001344551,0.0001665183,0.0005753043,0.001539074,0.0006750717,0.0008808693,0.0003151686,0.0008222939,0.01946087],"study_design_scores_gemma":[0.000003439558,0.0000209615,0.9969798,0.00003349926,0.00004030367,0.00005434459,0.0007954559,0.0005961824,0.0001734115,0.00004947546,0.001246304,0.000006911617],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9960433,0.001330293,0.0001431651,0.0003826568,0.00001126762,0.000004563278,0.0007865542,0.000006928252,0.001291283],"genre_scores_gemma":[0.9990051,0.0003328026,0.00009372011,0.00004534663,0.00001523476,0.000003246393,0.0004390863,0.000002564452,0.00006292034],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09786892,"threshold_uncertainty_score":0.1945985,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04542848732868213,"score_gpt":0.2856345947415389,"score_spread":0.2402061074128568,"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."}}