{"id":"W2523737905","doi":"10.1007/s10393-016-1162-4","title":"An Ecological and Human Biomonitoring Investigation of Mercury Contamination at the Aamjiwnaang First Nation","year":2016,"lang":"en","type":"article","venue":"EcoHealth","topic":"Mercury impact and mitigation studies","field":"Environmental Science","cited_by":14,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"National Center for Advancing Translational Sciences; National Institute of Environmental Health Sciences; National Oceanic and Atmospheric Administration; National Institutes of Health; National Center for Research Resources; School of Public Health, University of Michigan; Great Lakes Fishery Commission","keywords":"Animal ecology; Biomonitoring; Mercury (programming language); Contamination; Environmental science; Ecology; MERCURY EXPOSURE; Geography; Lichen; Public health; Environmental chemistry; Environmental protection; Biology; Chemistry; Medicine","routes":{"ca_aff":true,"ca_fund":false,"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":[],"consensus_categories":[],"category_scores_codex":[0.0004832086,0.00006208786,0.0000786265,0.00002010959,0.0003870686,0.000008171976,0.00005886781,0.00003608086,0.0004344724],"category_scores_gemma":[0.00006892579,0.00003457011,0.00001234136,0.00007143244,0.0002465595,0.0002381078,0.00005247302,0.0000284794,0.00007488995],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001787172,"about_ca_system_score_gemma":0.000005961406,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003263497,"about_ca_topic_score_gemma":0.001157954,"domain_scores_codex":[0.9993399,0.00008369799,0.000172326,0.0001365342,0.0001496451,0.0001178665],"domain_scores_gemma":[0.9995553,0.000125757,0.0001301448,0.0001030602,0.00001642099,0.00006928718],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000005855744,0.00002567097,0.9044446,0.00001292495,0.000004669293,1.963737e-7,0.001254887,0.000004475677,0.08648348,0.0005579703,0.001247176,0.005958065],"study_design_scores_gemma":[0.0001959652,0.0001514171,0.98838,0.00001344142,0.000004678544,0.000001155919,0.00008813336,0.0000289512,0.009036023,0.0004602488,0.001586567,0.00005342488],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9966153,0.00002290218,0.00004325592,0.001821966,0.0001209504,0.0001602235,0.000005369833,0.00001736013,0.001192678],"genre_scores_gemma":[0.9993924,0.0000647297,0.00006432883,0.0001114475,0.00006077651,0.00001375832,0.000005655244,0.000003938525,0.0002829424],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08393537,"threshold_uncertainty_score":0.4757168,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04566904233034919,"score_gpt":0.302587019103073,"score_spread":0.2569179767727238,"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."}}