{"id":"W1897418564","doi":"10.4236/as.2015.67066","title":"Exploring the Potential Impacts of Climate Variability on Spring Wheat Yield with the APSIM Decision Support Tool","year":2015,"lang":"en","type":"article","venue":"Agricultural Sciences","topic":"Climate change impacts on agriculture","field":"Agricultural and Biological Sciences","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Agriculture and Agri-Food Canada","funders":"Agriculture and Agri-Food Canada; Natural Sciences and Engineering Research Council of Canada","keywords":"Spring (device); Crop yield; Yield (engineering); Environmental science; Agronomy; Decision support system; Climate change; Computer science; Geology; Biology; Engineering; Oceanography","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.001619212,0.0007508154,0.0005780628,0.0007615602,0.0002933622,0.001454926,0.001102429,0.0005933515,0.003164161],"category_scores_gemma":[0.003331111,0.0003520778,0.0008021806,0.0005973897,0.0001823464,0.0009930937,0.0008487109,0.0005301812,0.0003735463],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001081287,"about_ca_system_score_gemma":0.001683632,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02142111,"about_ca_topic_score_gemma":0.0184065,"domain_scores_codex":[0.9995762,0.0001251897,0.00003919001,0.0000906448,0.0001204279,0.00004829367],"domain_scores_gemma":[0.9988263,0.0006905549,0.000133226,0.00005911261,0.0002421353,0.00004862526],"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":[0.0002559228,0.0001437028,0.01988376,0.0001339404,0.0001807544,0.0001330913,0.00009792822,0.9332712,0.001837748,0.002579108,0.002000841,0.03948206],"study_design_scores_gemma":[0.00001878188,0.00003644169,0.001274767,0.00001191131,0.00002060596,0.00001194685,0.00004416263,0.9959895,0.000905767,0.0008876144,0.0007874139,0.00001111002],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8044617,0.0001876531,0.1688673,0.0006946929,0.00006072331,0.0002000002,0.006741728,0.004646502,0.01413973],"genre_scores_gemma":[0.9156712,0.00008106982,0.0809975,0.00008625756,0.00001449023,0.0001453921,0.001970618,0.00007265908,0.0009607623],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02142111,"threshold_uncertainty_score":0.04259282,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1080993288879919,"score_gpt":0.261069409598051,"score_spread":0.1529700807100591,"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."}}