{"id":"W2123544490","doi":"10.1016/j.jglr.2010.09.002","title":"Temporal trends in near-shore sediment contaminant concentrations in the St. Clair River and potential long-term implications for fish tissue concentrations","year":2010,"lang":"en","type":"article","venue":"Journal of Great Lakes Research","topic":"Mercury impact and mitigation studies","field":"Environmental Science","cited_by":14,"is_retracted":false,"has_abstract":false,"ca_institutions":"Environment and Climate Change Canada; Ministry of the Environment, Conservation and Parks","funders":"","keywords":"Sediment; Environmental science; Hexachlorobenzene; Benthic zone; Food chain; Biomagnification; Mercury (programming language); Hydrology (agriculture); Bioaccumulation; Transect; Water quality; Environmental chemistry; Oceanography; Ecology; Geology; Pollutant; Chemistry; Biology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.0003147715,0.0001132387,0.0001199803,0.000638546,0.0002592252,0.0003683968,0.0002936989,0.0004310509,0.001288751],"category_scores_gemma":[0.0006323514,0.0001358496,0.0001690227,0.0005989216,0.0002315323,0.0002608499,0.0002275071,0.0002468558,0.0002878038],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008516143,"about_ca_system_score_gemma":0.0005755614,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.09854013,"about_ca_topic_score_gemma":0.2228155,"domain_scores_codex":[0.9998765,0.00001426686,0.00001206587,0.00003896666,0.00003032792,0.00002794258],"domain_scores_gemma":[0.9994614,0.00006819016,0.0001374697,0.00002875507,0.0002262206,0.00007791282],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004649124,0.0001043242,0.976211,0.00003193376,0.00009530931,0.000137701,0.0006102766,0.0004873482,0.01126246,0.0001654192,0.0005348385,0.009894452],"study_design_scores_gemma":[0.000001742908,0.0000531548,0.9987832,0.000003281129,0.00001396986,0.00003233892,0.0001769167,0.0003490941,0.0003258463,0.00001571757,0.0002412367,0.000003495846],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9990715,0.00008099635,0.0000369365,0.000048024,0.000001937892,0.000001878757,0.0002980302,0.000004393223,0.0004563259],"genre_scores_gemma":[0.9982723,0.00007747055,0.0001056542,0.00001911808,0.000003410502,0.000003987239,0.0004044369,0.00000214629,0.001111505],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09854013,"threshold_uncertainty_score":0.1959331,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05216738321509886,"score_gpt":0.3778700335898696,"score_spread":0.3257026503747708,"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."}}