{"id":"W2068915005","doi":"10.13031/2013.19493","title":"Pipeline vs. Truck Transport of Beef Cattle Manure","year":2005,"lang":"en","type":"article","venue":"2005 Tampa, FL July 17-20, 2005","topic":"Agricultural Engineering and Mechanization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Truck; Manure; Beef cattle; Environmental science; Manure management; Pipeline (software); Waste management; Engineering; Agronomy; Automotive engineering; Forestry; Geography","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0006862669,0.0005058937,0.0003217563,0.000662705,0.0005146133,0.001008132,0.0007566534,0.0007683765,0.009869557],"category_scores_gemma":[0.001036473,0.0001982144,0.0005136374,0.0008813743,0.0002821293,0.001232424,0.0005850936,0.0003956287,0.0005448709],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002472818,"about_ca_system_score_gemma":0.001232706,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02709764,"about_ca_topic_score_gemma":0.03300691,"domain_scores_codex":[0.9991789,0.0001667419,0.00004336732,0.0001460099,0.0002409173,0.0002239054],"domain_scores_gemma":[0.9992963,0.0002040116,0.00013986,0.00005512725,0.0002221829,0.00008254329],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.01895713,0.007024388,0.1268986,0.003279342,0.0004371893,0.00184939,0.0005285548,0.2135844,0.3032961,0.004170395,0.005901616,0.3140728],"study_design_scores_gemma":[0.001047451,0.0702268,0.3027558,0.0003724653,0.000835081,0.001317981,0.004322482,0.4023226,0.1761556,0.002005872,0.03833724,0.0003006699],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9922674,0.0002123353,0.00261792,0.00005565292,0.00004577138,0.0001649697,0.0004121369,0.0000477231,0.004175972],"genre_scores_gemma":[0.9905014,0.0002984137,0.003706862,0.00002913927,0.000009321182,0.00008126796,0.0005520914,0.00001475451,0.004806751],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02709764,"threshold_uncertainty_score":0.05387986,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004688999133227024,"score_gpt":0.1807534490099744,"score_spread":0.1760644498767474,"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."}}