{"id":"W3047127767","doi":"10.1016/j.envres.2020.110008","title":"Human biomonitoring of metals in sub-Arctic Dene communities of the Northwest Territories, Canada","year":2020,"lang":"en","type":"article","venue":"Environmental Research","topic":"Mercury impact and mitigation studies","field":"Environmental Science","cited_by":22,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Montréal; University of Waterloo","funders":"Global Water Futures; Natural Sciences and Engineering Research Council of Canada; Health Canada","keywords":"Biomonitoring; Mercury (programming language); Biomarker; Urine; Environmental health; Environmental chemistry; Percentile; Environmental science; Medicine; Biology; Chemistry; Internal medicine","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004315791,0.000248488,0.0002822173,0.001122711,0.002980636,0.0008939655,0.0005624933,0.0002625363,0.0008906552],"category_scores_gemma":[0.0007427312,0.0002404504,0.0001892468,0.002417951,0.0006025583,0.0002540854,0.0007352911,0.0002773492,0.0001858483],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01234514,"about_ca_system_score_gemma":0.01175293,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9945747,"about_ca_topic_score_gemma":0.998075,"domain_scores_codex":[0.9995521,0.00006086416,0.00001998577,0.00007652174,0.0001306247,0.0001599212],"domain_scores_gemma":[0.9992156,0.00004190459,0.00007405087,0.00002508854,0.0005186673,0.0001246148],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0000919128,0.00003629072,0.982478,0.00003929692,0.00005131706,0.0001206946,0.005127565,0.0001565333,0.0008523701,0.0001941581,0.00137139,0.009480534],"study_design_scores_gemma":[0.000003168888,0.00001569259,0.9881711,0.000025771,0.00001615438,0.00008285022,0.008402613,0.0001745504,0.0002432736,0.00003949573,0.00281689,0.000008413602],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9949227,0.0004752416,0.0001662027,0.0001521332,0.000006485328,0.00003069363,0.001833401,0.00000566442,0.002407503],"genre_scores_gemma":[0.9930951,0.0006651107,0.0003217183,0.00007279558,0.000002823829,0.0000230153,0.0008049267,0.000003683126,0.005010682],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01234514,"threshold_uncertainty_score":0.08957076,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0705859231367306,"score_gpt":0.3227704045597009,"score_spread":0.2521844814229703,"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."}}