{"id":"W2887809606","doi":"10.1021/acs.est.8b02286","title":"A Critical Time for Mercury Science to Inform Global Policy","year":2018,"lang":"en","type":"article","venue":"Environmental Science & Technology","topic":"Mercury impact and mitigation studies","field":"Environmental Science","cited_by":132,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada","funders":"National Institute of General Medical Sciences; National Institutes of Health; National Institute of Environmental Health Sciences; New York State Energy Research and Development Authority","keywords":"Mercury (programming language); Methylmercury; Biosphere; Environmental science; Food chain; Environmental chemistry; Environmental protection; Pollutant; Biomagnification; Bioaccumulation; Chemistry; Ecology; Biology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01695552,0.001467768,0.002378978,0.002113281,0.006709089,0.01786017,0.003206895,0.02154666,0.04231456],"category_scores_gemma":[0.02873312,0.0007038151,0.001197876,0.00246064,0.0149017,0.02915735,0.01325078,0.02963378,0.01356378],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01340712,"about_ca_system_score_gemma":0.03254393,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007771824,"about_ca_topic_score_gemma":0.007933189,"domain_scores_codex":[0.9902061,0.003471906,0.0004086635,0.001090763,0.002964274,0.001858334],"domain_scores_gemma":[0.9817293,0.006413677,0.0009326671,0.001979734,0.00442687,0.004517841],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00007052883,0.00007302836,0.000269262,0.0005346501,0.00004579841,0.000193908,0.001533616,0.0003010152,0.0006639192,0.3607755,0.5816835,0.05385534],"study_design_scores_gemma":[0.00001074345,0.00001876619,0.0001344129,0.0003961639,0.000007742913,0.00002738818,0.001122374,0.00005806327,0.0001061201,0.08883002,0.9092726,0.00001549786],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.000615646,0.02391643,0.001853634,0.9271441,0.01984771,0.00003382929,0.0002084338,0.0001554553,0.02622467],"genre_scores_gemma":[0.05465367,0.06025057,0.01418643,0.7780231,0.03178401,0.0003009464,0.00082041,0.0004895311,0.05949141],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.04231456,"threshold_uncertainty_score":0.1415563,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009908269028641104,"score_gpt":0.3098883213922749,"score_spread":0.2999800523636338,"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."}}