{"id":"W7056615647","doi":"","title":"FED AND NON-FED CATTLE PRODUCTION RETURNS IN RELATION TO TRADE FLOW","year":2004,"lang":"en","type":"article","venue":"SHAREOK (University of Oklahoma)","topic":"Particle accelerators and beam dynamics","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Production (economics); Consumption (sociology); Maximization; Investment (military); Terms of trade; Government (linguistics); Linear programming","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001894949,0.0002918266,0.0003207802,0.00127448,0.0002371756,0.00186085,0.0003971448,0.00034116,0.003402669],"category_scores_gemma":[0.005942522,0.0002943453,0.0006158025,0.001803713,0.0005444818,0.001685873,0.0006174999,0.0008134487,0.0004064607],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002266421,"about_ca_system_score_gemma":0.0004667392,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006583685,"about_ca_topic_score_gemma":0.009955144,"domain_scores_codex":[0.999347,0.0001884781,0.00003536745,0.00007017068,0.0001573809,0.0002015174],"domain_scores_gemma":[0.9947873,0.003167624,0.001225626,0.0002288751,0.0003952911,0.0001952352],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.001855383,0.0002753828,0.2099597,0.0002547621,0.0002626927,0.0006055717,0.000594018,0.6766903,0.00699703,0.04171634,0.002276654,0.05851216],"study_design_scores_gemma":[0.00008287912,0.001389257,0.6365142,0.0001595345,0.0002123189,0.0009889923,0.002355842,0.2936811,0.01580638,0.03209469,0.01654932,0.0001654294],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9783409,0.0005946096,0.004405587,0.0002053208,0.00001065348,0.00002032672,0.001478532,0.00006564074,0.01487852],"genre_scores_gemma":[0.9928371,0.0003299127,0.001049921,0.00002602488,0.000006015377,0.00001407347,0.0008539649,0.00003237984,0.004850533],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006583685,"threshold_uncertainty_score":0.01644415,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009608607344557596,"score_gpt":0.1814083287968344,"score_spread":0.1717997214522768,"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."}}