{"id":"W2073601687","doi":"10.1371/journal.pone.0113261","title":"Increasing Crop Diversity Mitigates Weather Variations and Improves Yield Stability","year":2015,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Agronomic Practices and Intercropping Systems","field":"Agricultural and Biological Sciences","cited_by":403,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University; University of Guelph","funders":"Grain Farmers of Ontario","keywords":"Tillage; Agronomy; Crop rotation; Crop diversity; Environmental science; Monocropping; Crop yield; Monoculture; Cropping system; Cropping; Mathematics; Crop; Biology; Agriculture; Ecology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003443621,0.00006108392,0.0001090655,0.000003551002,0.000197711,0.00006973463,0.00009416522,0.00004400088,0.0001191748],"category_scores_gemma":[0.000320104,0.00002493713,0.00002005431,0.00004640843,0.00004141322,0.000237025,0.0001990873,0.00006255823,0.00002103027],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002786371,"about_ca_system_score_gemma":0.000005172235,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006606767,"about_ca_topic_score_gemma":0.0004129893,"domain_scores_codex":[0.9994615,0.00007212401,0.00009874049,0.000155281,0.0001030212,0.0001093362],"domain_scores_gemma":[0.9995237,0.0002209115,0.00006078864,0.00003963011,0.00006215883,0.00009279742],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.00005048601,0.0004351225,0.3209135,0.00001391002,0.00007813464,6.023633e-7,0.0009361571,8.362206e-8,0.6754814,0.0001630813,0.0001498348,0.001777684],"study_design_scores_gemma":[0.0003552937,0.0007524686,0.9705974,0.0001905353,0.0001923665,0.000008120514,0.004562741,0.001255658,0.01855767,0.001343583,0.00169584,0.000488339],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9962276,0.0001072166,0.000004105259,0.001329964,0.00002995956,0.0001112761,0.00001540244,0.00003798568,0.002136474],"genre_scores_gemma":[0.9993551,0.00001124651,0.0002172676,0.00008960866,0.0001327935,0.000003068574,0.000005083239,4.104637e-7,0.0001854618],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6569237,"threshold_uncertainty_score":0.9987499,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.110076882343561,"score_gpt":0.2164456721888439,"score_spread":0.1063687898452829,"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."}}