{"id":"W2120354120","doi":"10.1890/11-2070.1","title":"Nutrients and defoliation increase soil carbon inputs in grassland","year":2012,"lang":"en","type":"article","venue":"Ecology","topic":"Soil Carbon and Nitrogen Dynamics","field":"Agricultural and Biological Sciences","cited_by":114,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph; McGill University","funders":"","keywords":"Nutrient; Agronomy; Litter; Grassland; Biomass (ecology); Grazing; Environmental science; Plant litter; Soil carbon; Palatability; Carbon sequestration; Soil organic matter; Organic matter; Nutrient cycle; Biology; Soil water; Ecology; Carbon dioxide","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":[0.0001585279,0.00006003466,0.00009187402,0.00001432907,0.00003222891,0.000007185027,0.00004220054,0.00009405801,0.00003113037],"category_scores_gemma":[0.00004914533,0.00002591446,0.00001471413,0.000119452,0.00002410336,0.00004651773,0.00003757389,0.00006153838,0.000007705533],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002762163,"about_ca_system_score_gemma":0.000003297426,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007609825,"about_ca_topic_score_gemma":0.01263226,"domain_scores_codex":[0.9994773,0.00006649125,0.0000920192,0.0001007126,0.00004696067,0.0002165584],"domain_scores_gemma":[0.9997749,0.00008521511,0.00003186746,0.00001937467,0.00001114784,0.00007747821],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001462762,0.00006092919,0.9948956,0.000001425082,0.000002087482,0.000001631706,0.00003962957,4.335057e-7,0.002389853,0.0001005586,0.00001428148,0.002478913],"study_design_scores_gemma":[0.0001940022,0.00006530502,0.998227,0.000001635484,0.000003918878,0.000007854138,0.00002746552,0.0004648695,0.0002416084,0.0003383869,0.0003630994,0.00006486366],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9977969,0.0001287722,6.28001e-8,0.000285016,0.000150651,0.00007153623,0.000003133554,0.00001697906,0.00154693],"genre_scores_gemma":[0.9995545,0.00006821259,0.000006937079,0.0001846426,0.0001157436,0.00001155409,0.00002050006,4.469296e-7,0.00003748048],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01187128,"threshold_uncertainty_score":0.7049099,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008910827039225907,"score_gpt":0.2043931446473298,"score_spread":0.1954823176081039,"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."}}