{"id":"W2398060488","doi":"10.1021/es072583j","title":"EPA releases list of potential endocrine disrupters | Consensus reached on prenatal exposures | Rewarding fertilizer pollution with crop subsidies | Order matters in pesticide exposures | News Briefs: Nano needs oversight ` Congress and carbon sequestration ` Low-cost greenhouse-gas controls ` Sowing carbon credits ` Cities for sustainability | Unleashing a dioxin legacy | Florida gators battle pesticides | Lead levels high in Canadian tap water","year":2007,"lang":"en","type":"article","venue":"Environmental Science & Technology","topic":"Chemical Analysis and Environmental Impact","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Subsidy; Pesticide; Environmental science; Fertilizer; Pollution; Agronomy; Political science; Biology","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":["metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.0005839783,0.0004189991,0.0005141719,0.0007101569,0.0002776707,0.00008825815,0.0003296942,0.0001755845,0.00005743794],"category_scores_gemma":[0.0003323376,0.0003444648,0.00006331349,0.0007155976,0.003706616,0.0005047312,0.0002216745,0.0002817466,0.000001151876],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002646192,"about_ca_system_score_gemma":0.00007119185,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.1505007,"about_ca_topic_score_gemma":0.08587428,"domain_scores_codex":[0.9966812,0.00007461992,0.0006535696,0.0008022101,0.0005652336,0.001223198],"domain_scores_gemma":[0.9990142,0.0001541574,0.0001957191,0.0003454651,0.00001192651,0.0002785584],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0003410896,0.0001281117,0.5427963,0.00002245803,0.00001849514,0.0001020251,0.0005917484,0.005942275,0.4487734,0.00001912579,0.000002529783,0.001262525],"study_design_scores_gemma":[0.001964592,0.0004816566,0.4191674,0.0001310105,0.00007934242,0.00007189027,0.007999769,0.001348093,0.5679993,0.0001971102,0.00002991409,0.0005298624],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9975464,0.00006199638,0.0000535976,0.001228883,0.0001073398,0.0008628722,0.0000527333,0.00002900416,0.00005718739],"genre_scores_gemma":[0.9995444,0.00001996678,0.0001737174,0.00007406222,0.00002752551,0.00007259895,0.00002908549,0.00003102539,0.0000276322],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1236288,"threshold_uncertainty_score":0.9999008,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006420450029147204,"score_gpt":0.2189674140694546,"score_spread":0.2125469640403074,"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."}}