{"id":"W2586748678","doi":"","title":"Proceedings of the 15th London Swine Conference: Production Technologies to Meet Market Demands, 1-2 April 2015, London, Ontario, Canada.","year":2015,"lang":"en","type":"article","venue":"","topic":"Metallurgy and Material Science","field":"Materials Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Production (economics); Library science; Political science; Media studies; Sociology; Economics; Computer science","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001153039,0.0001677833,0.0002527267,0.00005257856,0.0001227984,0.00008596327,0.0007769075,0.00008197817,0.001175154],"category_scores_gemma":[0.0006108398,0.00009973358,0.00002433029,0.000371474,0.0001941096,0.0003292112,0.0003686688,0.00006715106,0.00001658617],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002168686,"about_ca_system_score_gemma":0.001080847,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.5481936,"about_ca_topic_score_gemma":0.8964705,"domain_scores_codex":[0.9982534,0.00002251174,0.0003275321,0.0004229757,0.0006227054,0.0003508463],"domain_scores_gemma":[0.9989089,0.00001219709,0.0001818492,0.0002999592,0.000478783,0.0001183543],"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":[0.0001107129,0.00003201404,0.001472441,0.00003059808,0.000004315506,8.201927e-7,0.000272633,0.00001941675,0.6017928,0.005778654,0.3903533,0.0001323107],"study_design_scores_gemma":[0.0001877619,0.00008851081,0.002801618,0.00004646778,0.00001441034,0.00001731573,0.0005169179,0.00001770634,0.9221913,0.002604013,0.07132147,0.0001925279],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9675758,0.00002490932,0.00005109526,0.007386739,0.001758716,0.0005113216,0.000007105942,0.000123992,0.02256036],"genre_scores_gemma":[0.9764743,0.000004463996,0.001550509,0.0001350082,0.0000495672,0.0000349486,7.57776e-7,0.00000689642,0.02174355],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3482768,"threshold_uncertainty_score":0.9997379,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01823187436920093,"score_gpt":0.2197030864714735,"score_spread":0.2014712121022725,"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."}}