{"id":"W4415414224","doi":"10.1039/d5va00261c","title":"Industrial and public infrastructure as local sources of organic contaminants in the Arctic","year":2025,"lang":"en","type":"article","venue":"Environmental Science Advances","topic":"Arctic and Russian Policy Studies","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"Miljøstyrelsen","keywords":"Pollution; Arctic; Contamination; The arctic; Water pollution; Critical infrastructure; Air pollution","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00071213,0.0001249399,0.0001320052,0.00138199,0.001140777,0.001978229,0.0002745696,0.0003314423,0.002405497],"category_scores_gemma":[0.00110674,0.00009483727,0.0002065615,0.002653009,0.001315444,0.0006895182,0.001844576,0.0003379943,0.0001400858],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002808742,"about_ca_system_score_gemma":0.003894414,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.132386,"about_ca_topic_score_gemma":0.2536782,"domain_scores_codex":[0.9992483,0.0003777728,0.00001812917,0.00004743638,0.000118443,0.000189969],"domain_scores_gemma":[0.9989259,0.0002082605,0.0003564234,0.00003400515,0.000248637,0.000226796],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000342189,0.000248454,0.7837834,0.0006344913,0.0001349257,0.001541529,0.02573526,0.006653078,0.002682898,0.09511196,0.002628916,0.08050287],"study_design_scores_gemma":[0.000009595483,0.0001408961,0.8549231,0.000427821,0.0001193126,0.0003449625,0.09967286,0.002156385,0.0008887562,0.007962115,0.03332271,0.00003161107],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.973049,0.003344127,0.0006903155,0.001791005,0.00002036049,0.00000926279,0.0001803538,0.000009623248,0.02090584],"genre_scores_gemma":[0.9949739,0.003106125,0.0001804934,0.00004352409,0.00002164373,0.000004946158,0.00005728089,0.000003274927,0.001608868],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.132386,"threshold_uncertainty_score":0.2632308,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01010513613097274,"score_gpt":0.2740246889420601,"score_spread":0.2639195528110873,"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."}}