{"id":"W2036964443","doi":"10.1007/s13593-013-0161-x","title":"Higher yield and lower carbon emission by intercropping maize with rape, pea, and wheat in arid irrigation areas","year":2013,"lang":"en","type":"article","venue":"Agronomy for Sustainable Development","topic":"Agronomic Practices and Intercropping Systems","field":"Agricultural and Biological Sciences","cited_by":179,"is_retracted":false,"has_abstract":false,"ca_institutions":"Agriculture and Agri-Food Canada","funders":"","keywords":"Intercropping; Agronomy; Irrigation; Crop; Agriculture; Cropping; Yield (engineering); Crop yield; Cropping system; Environmental science; Biology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002325006,0.0001739887,0.0001891306,0.00002409098,0.0001699519,0.0002079763,0.00009194762,0.00008150504,0.000084708],"category_scores_gemma":[0.00001941122,0.00007546739,0.00001839598,0.00009243001,0.00003919133,0.0004608361,0.00009384098,0.00008762821,0.000001991177],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001684977,"about_ca_system_score_gemma":0.00002730678,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00395246,"about_ca_topic_score_gemma":0.0001747444,"domain_scores_codex":[0.9989244,0.00002261667,0.0002619411,0.0003470824,0.00007764103,0.0003662949],"domain_scores_gemma":[0.9995484,0.0001204121,0.0001000406,0.00004131544,0.00008687444,0.0001029498],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0013659,0.0007138916,0.4057029,0.001133452,0.0004117016,0.00006427561,0.008125726,0.00001332368,0.09791224,0.001590471,0.06423534,0.4187308],"study_design_scores_gemma":[0.001333401,0.0008291691,0.465778,0.0007109342,0.00002930306,0.00002537897,0.02296627,0.0003785182,0.006159994,0.0005434389,0.5001332,0.001112472],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9944107,0.0004128806,0.00003449986,0.001338544,0.00004551216,0.000772052,7.892116e-7,0.00002201857,0.002963022],"genre_scores_gemma":[0.9873405,0.00001645934,0.0002224402,0.0001228629,0.00004321063,0.000240036,0.00002822013,0.00000249303,0.01198376],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4358978,"threshold_uncertainty_score":0.5974964,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01027103269058449,"score_gpt":0.1922899841117233,"score_spread":0.1820189514211388,"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."}}