{"id":"W2914595591","doi":"10.1016/j.agrformet.2019.01.004","title":"Canola yield sensitivity to climate indicators and passive microwave-derived soil moisture estimates in Saskatchewan, Canada","year":2019,"lang":"en","type":"article","venue":"Agricultural and Forest Meteorology","topic":"Soil Moisture and Remote Sensing","field":"Environmental Science","cited_by":19,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Guelph; Agriculture and Agri-Food Canada","funders":"Agriculture and Agri-Food Canada; Natural Sciences and Engineering Research Council of Canada; Canadian Space Agency; Canada First Research Excellence Fund; Canola Council of Canada","keywords":"Canola; Environmental science; Water content; Moisture; Precipitation; Yield (engineering); Agronomy; Meteorology; Geography","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":[0.0007792193,0.0004632297,0.0003069086,0.001064404,0.001425116,0.00136403,0.001046478,0.0003271402,0.002336517],"category_scores_gemma":[0.001860701,0.0003131832,0.0004446759,0.002781738,0.0007483776,0.000432066,0.0008810909,0.0005671527,0.0003906046],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02766585,"about_ca_system_score_gemma":0.02053458,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9955543,"about_ca_topic_score_gemma":0.9982122,"domain_scores_codex":[0.999276,0.0001100456,0.0000393122,0.0001660865,0.0001569614,0.0002516253],"domain_scores_gemma":[0.9975182,0.0004149558,0.0001864167,0.000102388,0.001419154,0.0003589212],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000565119,0.0001530221,0.9694416,0.00005393778,0.0003986177,0.0004144048,0.0011977,0.004400767,0.00346312,0.0007401428,0.004703992,0.01446748],"study_design_scores_gemma":[0.00002035355,0.00001596109,0.9941334,0.00002536642,0.00006479907,0.00003646826,0.001938746,0.002102399,0.0003621396,0.00008853606,0.001187382,0.00002452511],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9909841,0.0002106678,0.0001461404,0.0003003878,0.00001291131,0.00002762038,0.002561355,0.00002990842,0.005726955],"genre_scores_gemma":[0.9942232,0.0002252196,0.0001690376,0.00009535851,0.000003141705,0.00001945394,0.001296386,0.00001230038,0.003955862],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02766585,"threshold_uncertainty_score":0.2007307,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003037299546876754,"score_gpt":0.1710946493761561,"score_spread":0.1680573498292794,"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."}}