{"id":"W7099933210","doi":"","title":"Intensive livestock operations, disembedding, and community polarization","year":2015,"lang":"en","type":"article","venue":"","topic":"Race, Genetics, and Society","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Livestock; Intensive farming; Agriculture; Local government; Government (linguistics); Quality (philosophy); Polarization (electrochemistry); Process (computing)","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":[0.003861582,0.0002396508,0.0002529387,0.001130813,0.009464473,0.005952962,0.0007172156,0.001041317,0.006649121],"category_scores_gemma":[0.005180929,0.0002009656,0.0001846215,0.001223099,0.01549228,0.003761256,0.01199352,0.002269043,0.0003363416],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004100636,"about_ca_system_score_gemma":0.004718,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01560034,"about_ca_topic_score_gemma":0.02690659,"domain_scores_codex":[0.9963934,0.001472753,0.0000639662,0.0003595931,0.000560036,0.001150183],"domain_scores_gemma":[0.9945569,0.001163882,0.0009833317,0.0005378966,0.0005982469,0.002159764],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.0002257035,0.000390473,0.1239355,0.00009725938,0.00004210498,0.001146396,0.1508263,0.0002908077,0.00196212,0.5799499,0.01625465,0.1248789],"study_design_scores_gemma":[0.00006618976,0.0001555335,0.1438363,0.0004609344,0.00003661622,0.001099443,0.313336,0.00107734,0.001371283,0.2892939,0.2491848,0.00008179879],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8201382,0.001187569,0.003260076,0.03461442,0.0001990416,0.00004352299,0.0000632081,0.00002133545,0.1404727],"genre_scores_gemma":[0.9933375,0.0003596832,0.0002304641,0.001307805,0.00004276257,0.00001441121,0.00001603445,0.000007277769,0.004683984],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01560034,"threshold_uncertainty_score":0.03101909,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02180874683216029,"score_gpt":0.27771441819203,"score_spread":0.2559056713598697,"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."}}