{"id":"W2120461939","doi":"10.5539/sar.v2n4p12","title":"Spatial Distribution of Calibrated WOFOST Parameters and Their Influence on the Performances of a Regional Yield orecasting System","year":2013,"lang":"en","type":"article","venue":"Sustainable Agriculture Research","topic":"Remote Sensing in Agriculture","field":"Environmental Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Agriculture and Agri-Food Canada","funders":"Belgian Federal Science Policy Office","keywords":"Anthesis; Environmental science; Crop; Yield (engineering); Crop yield; Spatial distribution; Baseline (sea); Spatial variability; Atmospheric sciences; Climatology; Physical geography; Agronomy; Geography; Mathematics; Statistics; Geology; Biology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.001599558,0.0004660322,0.0004461104,0.0003991625,0.000177658,0.0005802723,0.0006143736,0.0004118544,0.0003238855],"category_scores_gemma":[0.003938176,0.0002551871,0.0003763269,0.000401754,0.0002138721,0.0005173656,0.0003833806,0.000354674,0.0001128221],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006805164,"about_ca_system_score_gemma":0.0004589693,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01999338,"about_ca_topic_score_gemma":0.01215125,"domain_scores_codex":[0.9995956,0.0001210708,0.00002804401,0.000151195,0.00004601382,0.00005813071],"domain_scores_gemma":[0.9989635,0.0003981833,0.0001601555,0.0002255025,0.0002034221,0.00004922979],"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":[0.0004352777,0.00006924548,0.1249664,0.00003763114,0.0001111971,0.00009095014,0.000122422,0.8405348,0.009552254,0.0002233901,0.0002054624,0.02365098],"study_design_scores_gemma":[0.00007477446,0.0001343458,0.09265251,0.00001214281,0.00005352673,0.00003664555,0.00008076092,0.8966984,0.009626055,0.00007524301,0.0005274909,0.00002802136],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9938771,0.00005215771,0.005149411,0.00002394483,0.000006230431,0.00001000073,0.0001798834,0.0002629781,0.0004382032],"genre_scores_gemma":[0.997878,0.00001394067,0.001814868,0.000003972239,0.000001421641,0.000004011913,0.0002230108,0.00001206248,0.00004878011],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01999338,"threshold_uncertainty_score":0.03975397,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02214759227733177,"score_gpt":0.2294693237623794,"score_spread":0.2073217314850476,"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."}}