{"id":"W1513821594","doi":"10.2166/wst.2000.0566","title":"Sources, trends, implications and remediation of mercury contamination of lakes in remote areas of Canada","year":2000,"lang":"en","type":"article","venue":"Water Science & Technology","topic":"Mercury impact and mitigation studies","field":"Environmental Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada","funders":"","keywords":"Mercury (programming language); Environmental science; Biota; Environmental remediation; Remedial action; Deposition (geology); Sediment; Contamination; Environmental protection; Environmental engineering; Hydrology (agriculture); Environmental chemistry; Ecology; Geology; Chemistry","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002497318,0.0001709864,0.0001905185,0.001483518,0.001527922,0.0008463435,0.0004964243,0.000239251,0.0009920218],"category_scores_gemma":[0.0007893991,0.0001503925,0.0002166163,0.003032383,0.0007446301,0.000333932,0.0005421313,0.0004375955,0.00009823327],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01864396,"about_ca_system_score_gemma":0.01790227,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9926777,"about_ca_topic_score_gemma":0.9960911,"domain_scores_codex":[0.9995833,0.000020255,0.00002465601,0.00005685434,0.0001995498,0.0001152843],"domain_scores_gemma":[0.9988914,0.0000526473,0.0002516789,0.00001545396,0.0006244988,0.000164372],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001271292,0.00003852043,0.9678303,0.0001584483,0.00009264977,0.0002722134,0.002467537,0.0004216686,0.002318276,0.0003985519,0.001597643,0.02427724],"study_design_scores_gemma":[0.000002457289,0.00001088411,0.9963033,0.00001942568,0.00001786091,0.00005459634,0.00129442,0.0001626457,0.0002594986,0.00003161747,0.001836506,0.000006761177],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9908382,0.002927587,0.0001187258,0.001128297,0.000006131036,0.00001666836,0.001775953,0.00002282825,0.00316557],"genre_scores_gemma":[0.9954455,0.002078473,0.0002076349,0.000104654,0.000004828406,0.000004838168,0.0007261532,0.000003812574,0.001424159],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01864396,"threshold_uncertainty_score":0.135272,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006889108411989768,"score_gpt":0.2220816791942195,"score_spread":0.2151925707822297,"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."}}