{"id":"W4412925470","doi":"10.1071/cp24257","title":"The pros and cons of increasing soil organic matter in dryland cropping systems","year":2025,"lang":"en","type":"article","venue":"Crop and Pasture Science","topic":"Soil Carbon and Nitrogen Dynamics","field":"Agricultural and Biological Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Commonwealth Scientific and Industrial Research Organisation; European Commission; McGill University; Johns Hopkins University","keywords":"cons; Cropping; Dryland farming; Agroforestry; Environmental science; Organic matter; Soil organic matter; Agronomy; Earth science; Soil science; Geography; Geology; Soil water; Agriculture; Ecology; Biology; Computer science; Archaeology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005456089,0.00006210023,0.00009371073,0.00001699238,0.0003426553,0.0001724547,0.0001397392,0.00003491062,0.000003611033],"category_scores_gemma":[0.00007186258,0.00002014399,0.00001091782,0.0004947531,0.000573281,0.00006060343,0.00009477989,0.0000725233,6.252899e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000009837228,"about_ca_system_score_gemma":0.0000240212,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008926192,"about_ca_topic_score_gemma":0.001495009,"domain_scores_codex":[0.9994007,0.00004218921,0.0001189952,0.0001728263,0.0001024519,0.0001628778],"domain_scores_gemma":[0.999666,0.0001680469,0.00003961174,0.00004011339,0.0000486259,0.00003765504],"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":[0.00001478681,0.000008903568,0.483204,0.00001787785,0.000002507569,0.000001037521,0.000163958,0.000002211325,0.5122625,0.0006972221,0.00002763198,0.003597317],"study_design_scores_gemma":[0.00009687102,0.00002581398,0.9954059,0.00007871463,0.000004641814,0.00001775078,0.0008137466,0.001416212,0.001566406,0.000224437,0.0002817392,0.00006777049],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9968722,0.001069136,0.000002021099,0.0007985366,0.0001009667,0.0001077312,0.000002771422,0.000006403513,0.00104017],"genre_scores_gemma":[0.9996733,0.00004681897,0.000007771016,0.0001284143,0.0000181278,0.000003208942,4.938946e-7,2.721976e-7,0.000121574],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5122018,"threshold_uncertainty_score":0.2635462,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006465299956214025,"score_gpt":0.2101310023129365,"score_spread":0.2036657023567225,"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."}}