{"id":"W2132502593","doi":"10.1007/s13165-014-0060-8","title":"Managing nutrient in organic farming system: reliance on livestock production for nutrient management of arable farmland","year":2013,"lang":"en","type":"article","venue":"Organic Agriculture","topic":"Agriculture Sustainability and Environmental Impact","field":"Environmental Science","cited_by":36,"is_retracted":false,"has_abstract":false,"ca_institutions":"ASTER","funders":"","keywords":"Mixed farming; Environmental science; Organic farming; Livestock; Nutrient management; Agriculture; Arable land; Nutrient; Agroecology; Extensive farming; Agroforestry; Manure; Ecological farming; Integrated farming; Agronomy; Geography; Biology; Ecology; Forestry","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":[0.0002154352,0.0002928454,0.0002834206,0.00003954703,0.0001812242,0.00003502376,0.0002756538,0.0001316723,0.0005576898],"category_scores_gemma":[0.00002143289,0.000192537,0.00008343783,0.000679209,0.0000783551,0.0003369515,0.0001671333,0.0001972963,0.0002785337],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001275222,"about_ca_system_score_gemma":0.000004985403,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001513719,"about_ca_topic_score_gemma":0.00003986315,"domain_scores_codex":[0.9980758,0.00004998323,0.000399878,0.000625723,0.0003663866,0.000482243],"domain_scores_gemma":[0.9992986,0.00002388964,0.0002031821,0.0003363629,0.0000195705,0.0001184047],"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":[0.000441851,0.005317744,0.04250836,0.005193771,0.0003394745,0.00008063148,0.01051173,0.02439715,0.8208067,0.005614096,0.07027316,0.01451527],"study_design_scores_gemma":[0.004005285,0.001549106,0.6993411,0.002127236,0.0003066,0.0001419927,0.07757013,0.0006426458,0.1829571,0.004691299,0.02448846,0.002179139],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9918621,0.000134756,0.001077334,0.001162535,0.0002045515,0.002903218,0.000005368469,0.00007086866,0.002579261],"genre_scores_gemma":[0.9938025,0.0001324182,0.00072039,0.00006034138,0.00006691815,0.0002542067,0.0000224705,0.00002161819,0.004919169],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6568327,"threshold_uncertainty_score":0.785143,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004287638451630095,"score_gpt":0.1827980096336427,"score_spread":0.1785103711820126,"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."}}