{"id":"W2739872120","doi":"10.2134/cs2017.50.0311","title":"Potential of bioenergy cropping systems for soil and water quality improvement","year":2017,"lang":"en","type":"article","venue":"Crops & Soils","topic":"Bioenergy crop production and management","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Cropping; Environmental science; Agronomy; Crop rotation; Bioenergy; Agriculture; Agroforestry; Biofuel; Willow; Dryland farming; Soil quality; Agricultural engineering; Soil water; Crop; Geography; Engineering; Soil science; Biology; Biotechnology; Ecology","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":[0.000370817,0.0001066741,0.000175884,0.000008095731,0.0005505061,0.0002219335,0.0002124897,0.0000589773,0.00003513375],"category_scores_gemma":[0.0000226248,0.00003727035,0.00007421734,0.000016948,0.000157245,0.0001135123,0.0001821303,0.0000324506,0.000002922402],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001130121,"about_ca_system_score_gemma":0.000002975384,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005463223,"about_ca_topic_score_gemma":0.0003608468,"domain_scores_codex":[0.9990828,0.00002657972,0.0002499303,0.0002872672,0.0001207188,0.0002327033],"domain_scores_gemma":[0.9995221,0.00001062662,0.0001632409,0.000143001,0.0001001641,0.00006083366],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00003652188,0.00004741338,0.0001440754,0.00007061537,0.00003123079,5.979797e-7,0.00003221579,0.00004326742,0.8940045,0.001902626,0.0004924768,0.1031945],"study_design_scores_gemma":[0.001233468,0.0008308882,0.1165095,0.00007405856,0.00008858501,0.000006233486,0.001374325,0.0008359124,0.6075538,0.001377295,0.2694308,0.00068512],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9959152,0.000199363,0.000088586,0.002484511,0.0006624867,0.0002025913,0.00002248306,0.0000249825,0.0003998029],"genre_scores_gemma":[0.9969332,0.00008950982,0.00003386417,0.00009202937,0.0003670193,0.00003369991,0.00002269606,0.00000107348,0.002426918],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2864506,"threshold_uncertainty_score":0.8258796,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03012220651842016,"score_gpt":0.2579407728463022,"score_spread":0.2278185663278821,"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."}}