{"id":"W4408941132","doi":"10.1016/j.scitotenv.2025.179186","title":"Mercury in eastern coyotes from Nova Scotia, Canada: Effects of geography and trophic position","year":2025,"lang":"en","type":"article","venue":"The Science of The Total Environment","topic":"Mercury impact and mitigation studies","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada; Nova Scotia Department of Agriculture; Acadia University","funders":"Acadia University","keywords":"Nova scotia; Mercury (programming language); Geography; Trophic level; Nova (rocket); Ecology; Environmental science; Archaeology; Biology","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":[0.000187098,0.000327382,0.0002604314,0.0009349434,0.001683136,0.000664574,0.0004170497,0.0002699721,0.001124538],"category_scores_gemma":[0.0006182775,0.000257064,0.0001816584,0.001211681,0.0007107293,0.0001556466,0.0004871148,0.0003153782,0.000207487],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006552021,"about_ca_system_score_gemma":0.004934641,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9831187,"about_ca_topic_score_gemma":0.9960664,"domain_scores_codex":[0.9998393,0.00001185992,0.000008551029,0.00004317048,0.00003832331,0.00005863848],"domain_scores_gemma":[0.9992284,0.00005072687,0.0001434247,0.00002335897,0.0003478262,0.0002063575],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001122408,0.00003052537,0.9941533,0.00002372947,0.00003251684,0.0002190361,0.001414771,0.00005022551,0.001386289,0.00002593319,0.000276482,0.002274903],"study_design_scores_gemma":[0.000002256007,0.00001500542,0.9984514,0.000008658523,0.000007378674,0.00004761716,0.00117181,0.00004047112,0.00005454078,0.000003508764,0.000195362,0.000002095554],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9987171,0.0001208791,0.00002277389,0.00002415886,0.00000291528,0.00001126044,0.0005529537,0.000001366369,0.0005467017],"genre_scores_gemma":[0.9978224,0.0001910346,0.00009693441,0.00005257126,0.000001588809,0.000008826142,0.0005883452,0.000002482299,0.001235912],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01688129,"threshold_uncertainty_score":0.04753852,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00478386845598699,"score_gpt":0.1993666151731136,"score_spread":0.1945827467171266,"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."}}