{"id":"W1994616166","doi":"10.5194/acp-14-2219-2014","title":"Atmospheric mercury speciation and mercury in snow over time at Alert, Canada","year":2014,"lang":"en","type":"article","venue":"Atmospheric chemistry and physics","topic":"Mercury impact and mitigation studies","field":"Environmental Science","cited_by":67,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada","funders":"Aboriginal Affairs and Northern Development Canada","keywords":"Mercury (programming language); Snow; Environmental chemistry; Environmental science; Elemental mercury; Aerosol; Particulates; Chemistry; Atmospheric sciences; Meteorology; Geology; Physics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.0003332041,0.0003258792,0.0003311533,0.002162413,0.001592116,0.00106083,0.0005323757,0.0002231207,0.001093951],"category_scores_gemma":[0.0006021142,0.000174674,0.0003797392,0.004635875,0.0003487585,0.0003657033,0.0005398201,0.0002552626,0.0001471709],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01315297,"about_ca_system_score_gemma":0.01332398,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9921269,"about_ca_topic_score_gemma":0.9969916,"domain_scores_codex":[0.9996444,0.00001226045,0.00001870833,0.00005366265,0.0001910342,0.00007994385],"domain_scores_gemma":[0.9990252,0.00003021668,0.000109341,0.00001442165,0.0006957973,0.0001250586],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001009854,0.00001486692,0.9889696,0.00006347362,0.0001294767,0.0001870921,0.000820306,0.0003285764,0.002155299,0.00008293148,0.001114937,0.00603258],"study_design_scores_gemma":[0.000001521112,0.000007125657,0.9975445,0.00001064343,0.00001468228,0.00002625603,0.0005546515,0.0002193489,0.0002304313,0.00001094152,0.001374416,0.000005550653],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.983502,0.0007662939,0.000137826,0.00009809931,0.000008230464,0.00001867802,0.01254301,0.00002108697,0.002904758],"genre_scores_gemma":[0.9890484,0.0004800127,0.0003476829,0.00005493801,0.000004171883,0.00001025897,0.007926044,0.000007984933,0.00212045],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01315297,"threshold_uncertainty_score":0.09543192,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003994797263734967,"score_gpt":0.1899758488892524,"score_spread":0.1859810516255175,"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."}}