{"id":"W2473666281","doi":"10.1111/wre.12213","title":"Does yield loss due to weed competition differ between organic and conventional cropping systems?","year":2016,"lang":"en","type":"article","venue":"Weed Research","topic":"Organic Food and Agriculture","field":"Agricultural and Biological Sciences","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"Agriculture and Agri-Food Canada; University of Saskatchewan","funders":"Agriculture and Agri-Food Canada","keywords":"Weed; Agronomy; Competition (biology); Cropping system; Weed control; Crop rotation; Organic farming; Cropping; Environmental science; Crop yield; Yield (engineering); Biomass (ecology); Crop; Biology; Agriculture; Ecology; Materials science","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":[0.0008705014,0.0001430798,0.0002834742,0.0002826508,0.0002259528,0.0004070751,0.0002775243,0.0001372253,0.0009867023],"category_scores_gemma":[0.001249746,0.00008104829,0.0002278168,0.000316401,0.0003476294,0.0003613819,0.0003430168,0.0002425707,0.0001020822],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001111692,"about_ca_system_score_gemma":0.0004243602,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01115812,"about_ca_topic_score_gemma":0.03113599,"domain_scores_codex":[0.9996038,0.0000624998,0.00002403093,0.00008467464,0.0001224856,0.0001024136],"domain_scores_gemma":[0.9985738,0.0004147444,0.0004809307,0.00009309193,0.000206399,0.0002310283],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002967933,0.0006267891,0.8149019,0.0001882113,0.0003327987,0.0002219717,0.0004256858,0.0007052649,0.1506782,0.0001733054,0.0003286349,0.02844938],"study_design_scores_gemma":[0.000006730233,0.0006643309,0.9969267,0.000002877226,0.00001903132,0.00002823526,0.0001582261,0.000280349,0.001659039,0.00005144841,0.000199597,0.000003378372],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9995746,0.00005222111,0.00009199593,0.00001134116,0.000001353352,0.000004802571,0.0000559253,0.000001952465,0.0002058838],"genre_scores_gemma":[0.9995307,0.00002975699,0.00008879484,0.00002521489,0.000001561056,0.000005533981,0.0001485159,0.000001688099,0.0001683003],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01115812,"threshold_uncertainty_score":0.02218634,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04600615611250998,"score_gpt":0.2711863619940345,"score_spread":0.2251802058815245,"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."}}