{"id":"W2144331351","doi":"10.4067/s0718-95162014005000020","title":"Improving pasture growth and urea efficiency using N inhibitor, molybdenum and elemental sulphur","year":2014,"lang":"en","type":"article","venue":"Journal of soil science and plant nutrition","topic":"Soil Carbon and Nitrogen Dynamics","field":"Agricultural and Biological Sciences","cited_by":7,"is_retracted":false,"has_abstract":false,"ca_institutions":"Western University","funders":"University of Canterbury","keywords":"Urea; Pasture; Chemistry; Molybdenum; Urease; Fertilizer; Nitrification; Coated urea; Animal science; Nitrogen; Field experiment; Agronomy; Yield (engineering); Dry matter; Inorganic chemistry; Biology; Biochemistry; Metallurgy; Materials science; Organic chemistry","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001971903,0.0003144769,0.0003726601,0.0001661596,0.0002293464,0.0003322021,0.0004549972,0.0003077839,0.0006784597],"category_scores_gemma":[0.0001485871,0.0001454596,0.0002925441,0.000184801,0.0001853701,0.0003207936,0.000222651,0.0004239175,0.00009927363],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003868822,"about_ca_system_score_gemma":0.0003535977,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003179966,"about_ca_topic_score_gemma":0.007322709,"domain_scores_codex":[0.9999083,0.00001253796,0.000009746047,0.0000308845,0.00002047721,0.00001797317],"domain_scores_gemma":[0.9998592,0.00001777291,0.00003930979,0.00001277944,0.00001683613,0.0000540441],"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":[0.0004925021,0.0001364122,0.000889413,0.00005635672,0.00002386339,0.00002168144,0.00001821949,0.0002010029,0.9950445,0.00003038641,0.00002446114,0.003061196],"study_design_scores_gemma":[0.00008260772,0.002399294,0.02427716,0.00001502378,0.0001393888,0.0001215758,0.00006284331,0.003075358,0.9682224,0.00006078234,0.001531395,0.0000121366],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9988587,0.0003456932,0.0004613927,0.00001934548,0.000005799876,0.000005360603,0.00003472553,0.00001967315,0.0002493078],"genre_scores_gemma":[0.9962803,0.0002944441,0.00190069,0.00002773475,0.00000421972,0.000008197469,0.0001333012,0.00001041555,0.001340725],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003179966,"threshold_uncertainty_score":0.00632292,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008679722119628686,"score_gpt":0.1946642624755418,"score_spread":0.1859845403559131,"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."}}