{"id":"W2043226826","doi":"10.1016/j.scitotenv.2006.04.019","title":"Long-term trends in accumulated metals (Cd, Cu and Zn) and metallothionein in bivalves from lakes within a smelter-impacted region","year":2006,"lang":"en","type":"article","venue":"The Science of The Total Environment","topic":"Heavy metals in environment","field":"Environmental Science","cited_by":49,"is_retracted":false,"has_abstract":false,"ca_institutions":"Institut National de la Recherche Scientifique; Environment and Climate Change Canada; GDG Environnement; Université de Montréal; Université du Québec à Montréal","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Environmental chemistry; Environmental science; Smelting; Metallothionein; Cadmium; Trace metal; Ecosystem; Sediment; Metal; Ecology; Chemistry; Geology; 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":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.001507781,0.0003000574,0.0003560644,0.0001582851,0.0002018246,0.00005782926,0.0006979823,0.0000869366,0.000342386],"category_scores_gemma":[0.00005695584,0.000182912,0.00008014109,0.0006862042,0.003552607,0.000493977,0.001085294,0.0002655851,0.00003066381],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003438152,"about_ca_system_score_gemma":0.0000109122,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002402707,"about_ca_topic_score_gemma":0.0003440221,"domain_scores_codex":[0.9970284,0.0003043612,0.0005835527,0.0006847489,0.000907375,0.0004915557],"domain_scores_gemma":[0.9986809,0.0001117984,0.0002734601,0.0008180527,0.000001485169,0.0001142986],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.00008476508,0.0004741525,0.08232295,0.00000836248,0.00002841538,0.00001392299,0.00234586,0.1138682,0.7950888,0.00009963822,0.00001781459,0.005647144],"study_design_scores_gemma":[0.0005495641,0.00005379512,0.9728882,0.00003831991,0.00004215019,0.00001656097,0.00006976151,0.003608939,0.0216547,0.0008394422,0.00001537851,0.0002231746],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9978728,0.0003315602,0.00002769447,0.0008548982,0.00007987717,0.0003937141,0.00000811275,0.00001280224,0.0004185337],"genre_scores_gemma":[0.9984695,0.0001148392,0.0005515516,0.00002958612,0.00001356809,0.00002293787,0.000003504063,0.0000189956,0.0007755433],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8905653,"threshold_uncertainty_score":0.9991592,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01872764738366093,"score_gpt":0.2459188710330298,"score_spread":0.2271912236493689,"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."}}