{"id":"W4206106842","doi":"10.15809/irriga.2021v1n3p557-572","title":"USO DO SOFTWARE AQUACROP PARA SIMULAR A RESPOSTA DO FEIJÃO À DIFERENTES REGIMES DE IRRIGAÇÃO","year":2021,"lang":"pt","type":"article","venue":"Irriga","topic":"Irrigation Practices and Water Management","field":"Agricultural and Biological Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Discovery Air (Canada)","funders":"","keywords":"Humanities; Geography; Biology; Art","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":[0.0005678934,0.0007913117,0.0006395595,0.0005150528,0.0003093574,0.0006778719,0.0007468819,0.000583311,0.004715492],"category_scores_gemma":[0.00153155,0.0002740269,0.0007899107,0.0002427743,0.0002743796,0.0004444433,0.0006661983,0.0006760841,0.0007759716],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004382968,"about_ca_system_score_gemma":0.0006218152,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005592499,"about_ca_topic_score_gemma":0.004752689,"domain_scores_codex":[0.9997943,0.00003154819,0.00001614979,0.0000633807,0.00006902135,0.00002551986],"domain_scores_gemma":[0.9992487,0.0004381883,0.00006955591,0.0000489183,0.0001295098,0.00006518463],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.003180113,0.001584233,0.05290644,0.001429338,0.0004564055,0.0008740643,0.001188701,0.4181843,0.2806614,0.003610382,0.008715442,0.2272092],"study_design_scores_gemma":[0.0001789469,0.001540341,0.01486849,0.00006967653,0.0002196585,0.0001506436,0.0002151537,0.9144757,0.05751097,0.00141535,0.009258438,0.00009664352],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8022001,0.0006598695,0.1584685,0.0003466905,0.0002909757,0.0004490453,0.003069702,0.01874775,0.01576736],"genre_scores_gemma":[0.8929623,0.0004309499,0.09686551,0.000155238,0.00002419695,0.0007719424,0.001838463,0.0009678326,0.005983624],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005592499,"threshold_uncertainty_score":0.01577491,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04158218368914259,"score_gpt":0.2838304104469426,"score_spread":0.2422482267578001,"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."}}