{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001365127,0.0003576328,0.0003947376,0.0001407352,0.00005275807,0.00001413833,0.0002378147,0.0002394033,0.0006202493],"category_scores_gemma":[0.000009431778,0.0003209949,0.0001405855,0.0002925675,0.00002494424,0.0002511628,0.00001320269,0.0002907021,0.0003486623],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001435302,"about_ca_system_score_gemma":0.00002580003,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001256141,"about_ca_topic_score_gemma":0.0002786413,"domain_scores_codex":[0.9983132,0.00001086645,0.0005168635,0.0002722037,0.0003009815,0.0005858417],"domain_scores_gemma":[0.999306,0.00002107806,0.00006835307,0.0003086203,0.00007520109,0.0002207033],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001816396,0.00008915903,0.00006767227,0.0001393041,0.00004731453,0.0000059828,0.0005537159,0.7156696,0.01678758,0.0001046012,0.2629419,0.003574932],"study_design_scores_gemma":[0.0008119654,0.00003912381,0.001632721,0.00009395457,0.0000933481,0.00003619767,0.00005130505,0.04715837,0.04058328,0.00001146602,0.9089115,0.0005767266],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7255657,0.008977685,0.1771221,0.003580372,0.004109424,0.002304939,0.001637017,0.006034718,0.07066804],"genre_scores_gemma":[0.9244369,0.0004014437,0.008090119,0.0002111304,0.001678798,0.00003516962,0.0007828815,0.0001471365,0.06421642],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6685113,"threshold_uncertainty_score":0.9999242,"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."}}