{"id":"W2998844935","doi":"10.1016/j.marchem.2020.103755","title":"Elemental mercury in the marine boundary layer of North America: Temporal and spatial patterns","year":2020,"lang":"en","type":"article","venue":"Marine Chemistry","topic":"Mercury impact and mitigation studies","field":"Environmental Science","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Manitoba","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; ArcticNet","keywords":"Oceanography; Transect; Mercury (programming language); Arctic; Environmental science; Biogeochemical cycle; Submarine pipeline; Marine ecosystem; Bay; Mixed layer; Climatology; Atmospheric sciences; Geology; Ecosystem; Environmental chemistry; Ecology; Chemistry; Biology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0002158228,0.0001183251,0.0001575056,0.000695369,0.0003458693,0.0004844703,0.0002222315,0.0003110787,0.0006080838],"category_scores_gemma":[0.0004593839,0.0001518564,0.0001307472,0.001288783,0.0003150709,0.0003863626,0.0003981806,0.0001751891,0.00008097768],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007157677,"about_ca_system_score_gemma":0.0005626855,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.240299,"about_ca_topic_score_gemma":0.4073212,"domain_scores_codex":[0.9999255,0.00001201292,0.00000471717,0.00002525828,0.00001297466,0.00001944042],"domain_scores_gemma":[0.9996802,0.00006666256,0.0001003503,0.00001629069,0.00008643658,0.00005011887],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001208412,0.0000338768,0.9894323,0.00003407784,0.00009181828,0.00006389825,0.001078168,0.0001462224,0.002998116,0.0000560702,0.000319555,0.005624973],"study_design_scores_gemma":[8.869629e-7,0.000003672438,0.9991987,0.000002757355,0.0000074428,0.00001218059,0.0004185019,0.00007614147,0.00005672456,0.000008027533,0.0002138703,0.000001119462],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9989938,0.0002574735,0.00004029138,0.00005411642,0.000002990609,0.000001670759,0.0002247253,0.000003263261,0.0004217146],"genre_scores_gemma":[0.9987445,0.0002946858,0.0001051933,0.00002940156,0.000005435765,0.0000051533,0.0003581638,0.000002202922,0.0004551926],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.759701,"threshold_uncertainty_score":0.4778007,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01364572703100984,"score_gpt":0.2301481952955032,"score_spread":0.2165024682644934,"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."}}