{"id":"W2167883374","doi":"10.1039/c1em10225g","title":"Arsenic transformations in terrestrial small mammal food chains from contaminated sites in Canada","year":2011,"lang":"en","type":"article","venue":"Journal of Environmental Monitoring","topic":"Arsenic contamination and mitigation","field":"Environmental Science","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"Royal Military College of Canada; Defence Research and Development Canada; Stantec (Canada)","funders":"Natural Sciences and Engineering Research Council of Canada; Ministère de la Défense Nationale","keywords":"Arsenic; Phocoena; Food chain; Environmental chemistry; Harbour; Contamination; Wet weight; Chemistry; Biology; Ecology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0001594673,0.0001167878,0.0001640659,0.00007927852,0.00003789264,0.000007995661,0.0001597206,0.00004783881,0.0003713735],"category_scores_gemma":[0.00001546543,0.0001184689,0.00004878052,0.00009425251,0.00003842616,0.0003418583,0.0000369338,0.0002352421,0.00001023232],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001572605,"about_ca_system_score_gemma":0.00005281223,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.1370208,"about_ca_topic_score_gemma":0.5430844,"domain_scores_codex":[0.9988228,0.00006208002,0.0005355293,0.0001194607,0.0002639163,0.0001962002],"domain_scores_gemma":[0.9995678,0.00004909246,0.0002054196,0.00008146143,0.000001006647,0.00009524066],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00005459098,0.0001102413,0.9564801,9.808168e-7,0.00001148311,0.00006185541,0.002727858,0.000173644,0.02436577,0.000002282661,0.000007134905,0.01600409],"study_design_scores_gemma":[0.001344132,0.0001003916,0.9789032,0.00003571916,0.00001093289,0.00001142038,0.003146815,0.0003935494,0.01580264,0.00003865347,0.00009527755,0.0001172759],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9986706,0.00005503611,0.00009158067,0.00003460293,0.0003651713,0.0001234041,0.00001279291,0.000003866368,0.0006429389],"genre_scores_gemma":[0.9993331,0.00006085486,0.0004727686,0.00001610915,0.00007136068,0.00000444788,0.000004854494,0.000009211295,0.00002723742],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4060636,"threshold_uncertainty_score":0.8687258,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02302221904305603,"score_gpt":0.1857451291996953,"score_spread":0.1627229101566393,"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."}}