{"id":"W4245873576","doi":"10.13031/trans.58.11326","title":"Model for Estimating Feedlot Manure Quantity and Nutrient Content","year":2015,"lang":"en","type":"article","venue":"Transactions of the ASABE","topic":"Phosphorus and nutrient management","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Feedlot; Manure; Nutrient; Phosphorus; Manure management; Nitrogen; Animal science; Agronomy; Fertilizer; Environmental science; Bedding; Chemistry; Biology; Horticulture","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001907743,0.00006668321,0.00008604338,0.00001028696,0.000124299,0.00001071872,0.0001505516,0.0000207115,0.00002577853],"category_scores_gemma":[0.00001164504,0.00004770431,0.00005555815,0.0000732707,0.00009635791,0.0001026601,0.00002859075,0.00004610695,0.000006012588],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005508272,"about_ca_system_score_gemma":0.000005241242,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000237324,"about_ca_topic_score_gemma":0.00007352782,"domain_scores_codex":[0.9994584,0.00001014867,0.0001280878,0.00012724,0.0001597418,0.0001163684],"domain_scores_gemma":[0.9996741,0.00001669441,0.00005441153,0.0001873304,0.00001020273,0.00005727267],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003361533,0.0009216727,0.01521053,0.0001089807,0.00009631589,3.132794e-7,0.003615042,0.948151,0.004244206,0.004335434,0.009225267,0.01375508],"study_design_scores_gemma":[0.001028944,0.0001196274,0.00611622,0.000023385,0.00007128416,0.000001702817,0.0003490523,0.9802527,0.004413871,0.006561457,0.0009377591,0.0001239577],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3865765,0.00003653987,0.611876,0.0005277052,0.0001393255,0.0003431873,0.00001522576,0.00001380851,0.0004716358],"genre_scores_gemma":[0.9771449,0.000008874038,0.02157608,0.00006850322,0.000005269701,0.00003134169,6.431407e-7,0.000005817766,0.001158598],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5905683,"threshold_uncertainty_score":0.1945325,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08419842406563634,"score_gpt":0.2588221461017154,"score_spread":0.1746237220360791,"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."}}