{"id":"W2111618370","doi":"10.5539/jas.v7n3p79","title":"Evaluating CERES-Maize Model Using Planting Dates and Nitrogen Fertilizer in Zambia","year":2015,"lang":"en","type":"article","venue":"Journal of Agricultural Science","topic":"Crop Yield and Soil Fertility","field":"Agricultural and Biological Sciences","cited_by":50,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Sowing; Anthesis; Fertilizer; Biomass (ecology); Agronomy; Growing season; Phenology; Crop simulation model; Mathematics; Field experiment; Environmental science; DSSAT; Yield (engineering); Grain yield; Nitrogen; Leaf area index; Crop yield; Biology; Cultivar; Chemistry","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"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":[0.001867838,0.0001203637,0.0002191151,0.00002737931,0.000223202,0.0001981404,0.0003573615,0.00005048457,0.00001138139],"category_scores_gemma":[0.0005104414,0.00003758153,0.00005787032,0.0005918627,0.0001523645,0.0008181665,0.0001478123,0.0001907714,0.000001127201],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009119343,"about_ca_system_score_gemma":0.00006506152,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00028849,"about_ca_topic_score_gemma":0.0002760173,"domain_scores_codex":[0.9983566,0.00006294647,0.000412641,0.0002187685,0.0006170828,0.0003319297],"domain_scores_gemma":[0.9990199,0.0001047522,0.0002445771,0.00003480703,0.0003524843,0.000243466],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0000560024,0.00004216216,0.0956709,0.000003243914,0.000003193163,0.00000592332,0.0005456165,0.002581802,0.8940563,0.00001506984,0.00003341836,0.00698642],"study_design_scores_gemma":[0.0003313904,0.0002265422,0.9634133,0.00008267684,0.00001504731,0.0002088677,0.002616157,0.02178534,0.009761513,0.001345653,0.0000175893,0.0001959205],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9990141,0.0002385546,0.000002138584,0.0003274301,0.0001031691,0.00007635831,0.000002844151,0.000008472981,0.0002268833],"genre_scores_gemma":[0.9986671,0.00001066727,0.001126807,0.00004926421,0.0001277906,4.670528e-7,9.545656e-7,4.112169e-7,0.00001656057],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8842947,"threshold_uncertainty_score":0.1910673,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1493212423476684,"score_gpt":0.3299986998894245,"score_spread":0.1806774575417562,"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."}}