{"id":"W2953684647","doi":"10.1016/j.envint.2019.104971","title":"Corn (Zea mays L.): A low methylmercury staple cereal source and an important biospheric sink of atmospheric mercury, and health risk assessment","year":2019,"lang":"en","type":"article","venue":"Environment International","topic":"Mercury impact and mitigation studies","field":"Environmental Science","cited_by":34,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada","funders":"K. C. Wong Education Foundation; China Postdoctoral Science Foundation; Chinese Academy of Sciences; National Natural Science Foundation of China","keywords":"Mercury (programming language); Methylmercury; Environmental science; Agronomy; Sink (geography); Contamination; Environmental chemistry; Staple food; Chemistry; Agriculture; Bioaccumulation; Biology; Ecology; Geography","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000546833,0.0002176703,0.000281951,0.00001365258,0.0001187273,0.00003445479,0.0001668416,0.00005238709,0.004672335],"category_scores_gemma":[0.00001113007,0.0001964169,0.00005025186,0.00007104423,0.0002476882,0.0003277537,0.0002936802,0.0001488758,0.00006535448],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002369823,"about_ca_system_score_gemma":0.00002006058,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001151101,"about_ca_topic_score_gemma":0.00004959687,"domain_scores_codex":[0.9981766,0.0001002292,0.0004587712,0.000441518,0.0005608065,0.0002620539],"domain_scores_gemma":[0.9990647,0.00005798063,0.0004301744,0.0002424412,0.000005889768,0.0001988576],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002373687,0.0002138564,0.9621838,0.00001639818,0.00009359104,0.000001700479,0.00115816,0.0006924287,0.004133384,0.0001484534,0.0006533619,0.03068111],"study_design_scores_gemma":[0.000794473,0.0004333691,0.9740712,0.0000193991,0.00002745693,0.00001358714,0.001236479,0.01111925,0.0003239094,0.0003308454,0.01136419,0.0002658181],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9949504,0.0002658348,0.001988757,0.0006182927,0.000172293,0.0003491143,0.00009991872,0.00002136421,0.001534082],"genre_scores_gemma":[0.9889336,0.001966917,0.007898198,0.0003354271,0.0000376192,0.00001858398,0.00005878172,0.0000222062,0.0007286687],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03041529,"threshold_uncertainty_score":0.9962375,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01118588398838461,"score_gpt":0.2760766233489851,"score_spread":0.2648907393606005,"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."}}