{"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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00009090435,0.0001849612,0.0002060875,5.654876e-8,0.0001362973,0.00001849581,0.00007122335,0.00005545836,0.003474274],"category_scores_gemma":[0.00002893063,0.0001800066,0.00002321574,0.0001661768,0.0001317066,0.0001388924,0.0001086569,0.00009641895,0.00004131021],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002121729,"about_ca_system_score_gemma":0.00002220765,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02954919,"about_ca_topic_score_gemma":0.008867756,"domain_scores_codex":[0.9990686,0.00002457174,0.0001702123,0.0002900746,0.0002100599,0.0002365492],"domain_scores_gemma":[0.9995317,0.0000987959,0.00007751837,0.0001620185,0.000006288769,0.0001236299],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00005749748,0.0001175779,0.4928378,0.0001205538,0.00006997812,0.0000107198,0.00139878,0.001349177,0.06984375,0.00004505082,0.04267341,0.3914757],"study_design_scores_gemma":[0.001377534,0.00004596089,0.7734168,0.0000644819,0.00006560233,0.00002133063,0.0001620711,0.06013435,0.01198757,0.0009474858,0.1507951,0.0009817028],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9802797,0.0001519458,0.00007324799,0.0001420015,0.00003728909,0.00007441769,0.000006221527,0.00001534849,0.01921985],"genre_scores_gemma":[0.9886233,0.0001882366,0.0009775229,0.0004008641,0.0001293461,0.000009795874,0.00002138832,0.00001587895,0.009633675],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.390494,"threshold_uncertainty_score":0.9974367,"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."}}