{"id":"W2029456433","doi":"10.1139/a03-004","title":"Natural emissions of mercury to the atmosphere in Canada","year":2003,"lang":"en","type":"article","venue":"Environmental Reviews","topic":"Mercury impact and mitigation studies","field":"Environmental Science","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Environmental science; Mercury (programming language); Emission inventory; Aeolian processes; Atmospheric sciences; Terrestrial ecosystem; Fugitive emissions; Hydrology (agriculture); Physical geography; Greenhouse gas; Ecosystem; Air quality index; Ecology; Meteorology; Geography; Oceanography; Geology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002556342,0.00011538,0.0001945099,0.000002984676,0.00007254015,0.000002862082,0.0001553468,0.00001336651,0.00305247],"category_scores_gemma":[0.00009629105,0.00007075952,0.00004708042,0.0001493803,0.00005996463,0.0000556507,0.00007712071,0.00009757726,0.0004181504],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004314598,"about_ca_system_score_gemma":0.00002518466,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.09656087,"about_ca_topic_score_gemma":0.4007109,"domain_scores_codex":[0.9989998,0.0001259439,0.0002992677,0.0001564211,0.0002283402,0.0001901911],"domain_scores_gemma":[0.9995567,0.00004139194,0.0000775417,0.0002330019,1.567946e-7,0.00009120737],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000008356803,0.00009620414,0.725308,0.00001342209,0.00001495436,0.000007012975,0.001712867,0.0003578425,0.02169948,0.00004366207,0.1329278,0.1178104],"study_design_scores_gemma":[0.0000739544,0.000009566227,0.2038368,0.00001958152,0.000005612666,0.000003002957,0.0005199216,0.000008842399,0.001462209,0.00001285481,0.793958,0.0000897129],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9795182,0.008502807,0.00001180598,0.0005358014,0.0001654578,0.0005180983,0.000006417922,0.000002334737,0.01073905],"genre_scores_gemma":[0.9954492,0.002023057,0.0003312641,0.0009287022,0.000006386769,0.00003448538,0.000002205139,0.000006246943,0.001218449],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6610302,"threshold_uncertainty_score":0.9978589,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01312406318762647,"score_gpt":0.2382356682021674,"score_spread":0.2251116050145409,"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."}}