{"id":"W2800622002","doi":"10.1021/acs.est.7b02600","title":"Cities’ Role in Mitigating United States Food System Greenhouse Gas Emissions","year":2018,"lang":"en","type":"article","venue":"Environmental Science & Technology","topic":"Agriculture Sustainability and Environmental Impact","field":"Environmental Science","cited_by":51,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; American Chemistry Council; U.S. Environmental Protection Agency","keywords":"Greenhouse gas; Urbanization; Natural resource economics; Carbon footprint; Per capita; Food systems; Environmental science; Agriculture; Business; Agricultural economics; Population; Life-cycle assessment; Government (linguistics); Environmental protection; Environmental engineering; Production (economics); Food security; Economic growth; Economics; Geography; Environmental health","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0005309926,0.0003350434,0.0002554152,0.0004569337,0.0008788091,0.00005123809,0.00100539,0.0002307587,0.001181839],"category_scores_gemma":[0.00006795759,0.0002824822,0.00005990547,0.002643329,0.007772351,0.0006311194,0.001262363,0.0004002008,0.000704792],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002886241,"about_ca_system_score_gemma":0.00001916323,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004759717,"about_ca_topic_score_gemma":0.0002359738,"domain_scores_codex":[0.9968037,0.00006564739,0.0004254055,0.0009016132,0.0006624823,0.001141122],"domain_scores_gemma":[0.9989077,0.0000351956,0.0001475129,0.0006052408,0.000003356787,0.0003009368],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00004160503,0.0007456138,0.6690712,0.00001880145,0.00001625627,0.00006288484,0.005773416,0.00308207,0.3010434,0.000888311,0.0003928809,0.01886358],"study_design_scores_gemma":[0.002035962,0.004145283,0.4683784,0.0001871608,0.00005160416,0.0005019513,0.2096838,0.01320546,0.2501554,0.01026325,0.03914507,0.002246691],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9935493,0.00004421986,0.00009327666,0.000670202,0.00008568441,0.0004343708,0.00002449737,0.0002578293,0.004840581],"genre_scores_gemma":[0.9986071,0.00002680076,0.0008035956,0.0001878715,0.00003541877,0.00005514541,0.00001953168,0.00002382259,0.0002407218],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2039104,"threshold_uncertainty_score":0.9999627,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004196139561691486,"score_gpt":0.2002612629600257,"score_spread":0.1960651233983343,"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."}}