{"id":"W4409165503","doi":"10.3389/fenvc.2025.1505053","title":"Elemental atmospheric deposition around North America’s largest metal processor of electronic waste (Horne Smelter, Canada)","year":2025,"lang":"en","type":"article","venue":"Frontiers in Environmental Chemistry","topic":"Lichen and fungal ecology","field":"Agricultural and Biological Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Université du Québec en Abitibi-Témiscamingue; Université du Québec à Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Smelting; Deposition (geology); Electronic waste; Environmental science; Archaeology; Metallurgy; Waste management; Environmental chemistry; Materials science; Geography; Engineering; Geology; Chemistry; Sediment","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":[0.00008539567,0.0002324813,0.0002070406,0.0007244908,0.001374266,0.000727525,0.0003129722,0.0002209626,0.0008738805],"category_scores_gemma":[0.0001492333,0.000151067,0.0001257512,0.0009731923,0.0002846837,0.0001597096,0.0003651774,0.0001688563,0.0001392518],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005494293,"about_ca_system_score_gemma":0.004739726,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9542044,"about_ca_topic_score_gemma":0.9827204,"domain_scores_codex":[0.9998739,0.000005459804,0.000003108418,0.00003497734,0.00005559295,0.00002706081],"domain_scores_gemma":[0.9998078,0.00001044148,0.00001968775,0.000003429869,0.0001267916,0.00003185852],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002001863,0.00005567479,0.8994781,0.0001231929,0.00006697114,0.000455125,0.002122265,0.000538267,0.07285987,0.0001172494,0.0008397719,0.0231434],"study_design_scores_gemma":[0.000002523178,0.00001887856,0.9961021,0.00001003373,0.0000103732,0.00004626467,0.0006997256,0.0002257238,0.001937606,0.000009398934,0.0009335033,0.000003845081],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9967718,0.0002434256,0.0001433908,0.00003325163,0.000002885808,0.00001283608,0.0006520964,0.00001439851,0.002125833],"genre_scores_gemma":[0.9965529,0.0003040611,0.0005077334,0.00003678531,0.000003097686,0.000007425032,0.0005336806,0.000004811572,0.002049507],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04579562,"threshold_uncertainty_score":0.0921306,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.001681932334703229,"score_gpt":0.1487564443003253,"score_spread":0.1470745119656221,"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."}}