{"id":"W2060468368","doi":"10.1016/s1352-2310(02)00917-2","title":"Temporal and spatial variability of total gaseous mercury in Canada: results from the Canadian Atmospheric Mercury Measurement Network (CAMNet)","year":2003,"lang":"en","type":"article","venue":"Atmospheric Environment","topic":"Mercury impact and mitigation studies","field":"Environmental Science","cited_by":161,"is_retracted":false,"has_abstract":false,"ca_institutions":"Environment and Climate Change Canada","funders":"","keywords":"Sunrise; Noon; Diel vertical migration; Environmental science; Mercury (programming language); Atmospheric sciences; Sunset; Seasonality; Diurnal cycle; Diurnal temperature variation; Daytime; Climatology; Ecology; Oceanography; Geology","routes":{"ca_aff":true,"ca_fund":false,"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":[0.001247234,0.000305017,0.0003676573,9.940073e-7,0.0002830667,0.00001837405,0.0001834377,0.00008179752,0.001749772],"category_scores_gemma":[0.0002144478,0.000242628,0.00005370948,0.0002137905,0.0003314544,0.00008676982,0.0001278861,0.0002203487,0.00002895253],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003028214,"about_ca_system_score_gemma":0.0005300854,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9971955,"about_ca_topic_score_gemma":0.9974779,"domain_scores_codex":[0.9969467,0.0004141675,0.0006538611,0.000538851,0.0008375377,0.0006089039],"domain_scores_gemma":[0.9986734,0.0002318795,0.0002248274,0.0005366599,0.000008441214,0.0003247435],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00004195937,0.00006001729,0.9581977,0.000004019847,0.0000572888,0.00001772419,0.0007171938,0.03062664,0.00008674557,0.0000209937,0.004146574,0.006023188],"study_design_scores_gemma":[0.0006868874,0.00006127247,0.9746257,0.00001881079,0.00004532021,0.000005508094,0.0004321802,0.001894967,0.00005254415,0.0002077204,0.02166703,0.0003020426],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9931258,0.0007919001,0.0003703177,0.0007221251,0.0002684178,0.0006150574,0.00006650409,0.000009017223,0.004030868],"genre_scores_gemma":[0.996021,0.0001722604,0.003205334,0.0004087105,0.00004203086,0.0000386705,0.00001521472,0.00002017519,0.00007658541],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02873168,"threshold_uncertainty_score":0.9991628,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01160144229465768,"score_gpt":0.181787224426301,"score_spread":0.1701857821316433,"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."}}