{"id":"W1998686709","doi":"10.1007/s10661-006-7674-6","title":"Reduced Metals Concentrations of Water, Sediment and Hyalella Azteca from Lakes in the Vicinity of the Sudbury Metal Smelters, Ontario, Canada","year":2006,"lang":"en","type":"article","venue":"Environmental Monitoring and Assessment","topic":"Heavy metals in environment","field":"Environmental Science","cited_by":12,"is_retracted":false,"has_abstract":false,"ca_institutions":"Environment and Climate Change Canada","funders":"","keywords":"Hyalella azteca; Bioaccumulation; Environmental chemistry; Sediment; Amphipoda; Environmental science; Ecotoxicology; Water quality; Surface water; Water pollution; Bay; Hydrology (agriculture); Chemistry; Crustacean; Geology; Ecology; Environmental engineering; Oceanography; Biology","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":[],"consensus_categories":[],"category_scores_codex":[0.0004219741,0.0002185917,0.0002735438,0.0000161496,0.0001674885,0.00001793866,0.0002487552,0.0000521858,0.0002665846],"category_scores_gemma":[0.000003544561,0.000133016,0.00005512421,0.00005378393,0.0004294819,0.0001097853,0.000290738,0.0002390847,0.000001367276],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006419178,"about_ca_system_score_gemma":0.00003460846,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.6569341,"about_ca_topic_score_gemma":0.1597376,"domain_scores_codex":[0.9979628,0.0002362107,0.0004750102,0.0003417864,0.0007022767,0.0002819377],"domain_scores_gemma":[0.9992938,0.000123187,0.000149056,0.0003722522,9.992809e-7,0.00006071947],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000006362311,0.0001798817,0.6449512,0.000005328485,0.0000303691,0.000004313771,0.0007494469,0.0009938038,0.3524227,0.00001067569,0.00003914154,0.0006068565],"study_design_scores_gemma":[0.0003069215,0.00004299051,0.7479783,0.00001873555,0.00005626316,0.000002551317,0.0009427517,0.0000397121,0.2488579,0.000084358,0.001552871,0.0001166096],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9980763,0.0002855084,0.00001080937,0.0002196374,0.0002533594,0.0003817468,0.0000492161,0.000003474144,0.0007199243],"genre_scores_gemma":[0.9989909,0.00008841397,0.000626459,0.00002624014,0.00004123558,0.0000371871,0.00001688277,0.00001150038,0.0001612109],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4971965,"threshold_uncertainty_score":0.855595,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009257405600942528,"score_gpt":0.2220769015133824,"score_spread":0.2128194959124398,"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."}}