{"id":"W4402414391","doi":"10.1021/acs.est.4c07649","title":"Atmospheric Mercury Concentrations and Isotopic Compositions Impacted by Typical Anthropogenic Mercury Emissions Sources","year":2024,"lang":"en","type":"article","venue":"Environmental Science & Technology","topic":"Mercury impact and mitigation studies","field":"Environmental Science","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada","funders":"Youth Innovation Promotion Association of the Chinese Academy of Sciences; Chinese Academy of Sciences; Guizhou Science and Technology Department; National Natural Science Foundation of China","keywords":"Mercury (programming language); Environmental chemistry; Environmental science; Atmospheric emissions; Environmental protection; Atmospheric sciences; Chemistry; Geology","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":[0.00006019195,0.0001902919,0.0001182022,0.0003109957,0.0002445331,0.0001850205,0.0001401096,0.0002103453,0.0004162684],"category_scores_gemma":[0.00008750558,0.0000893317,0.0001461098,0.0004665816,0.0001186157,0.0001141805,0.0001696293,0.0001244468,0.00007760852],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002075957,"about_ca_system_score_gemma":0.0001375059,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009566599,"about_ca_topic_score_gemma":0.01793393,"domain_scores_codex":[0.999918,0.000006432567,0.00000358334,0.0000298319,0.0000297027,0.00001246957],"domain_scores_gemma":[0.9999547,0.000005231413,0.00001435185,0.000003620136,0.00001630096,0.000005785254],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003247058,0.00006895041,0.67883,0.00007966482,0.00012921,0.0005570047,0.0002200647,0.001798339,0.3003466,0.00008571758,0.0002452548,0.01731455],"study_design_scores_gemma":[0.000003135389,0.00007806127,0.9812503,0.000002348555,0.00002546129,0.000118214,0.0001267949,0.0009084402,0.01701917,0.00003996538,0.0004210092,0.000007068006],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9989771,0.00004809082,0.0002110341,0.000005318518,0.000001791486,0.000003147213,0.0002126327,0.0000133907,0.0005275478],"genre_scores_gemma":[0.9991757,0.00006728881,0.0002977331,0.000009028309,0.000003071487,0.000004122179,0.0002173655,0.000004073505,0.0002214646],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009566599,"threshold_uncertainty_score":0.01902187,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005836323245461276,"score_gpt":0.2492469498165009,"score_spread":0.2434106265710397,"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."}}