{"id":"W4403709803","doi":"10.1139/as-2024-0045","title":"Snow as an indicator of atmospheric transport of anthropogenic particles (microplastics and microfibers) from urban to Arctic regions","year":2024,"lang":"en","type":"article","venue":"Arctic Science","topic":"Microplastics and Plastic Pollution","field":"Environmental Science","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Government of Northwest Territories; Assembly of First Nations; University of Waterloo; University of Toronto; Environment and Climate Change Canada","funders":"Northern Contaminants Program","keywords":"Microplastics; Snow; Environmental science; Arctic; The arctic; Atmospheric sciences; Environmental chemistry; Meteorology; Geography; Oceanography; Geology; Chemistry","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"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":[0.0001147528,0.0001839781,0.00009791473,0.0005674455,0.0005169595,0.0004379717,0.0001312175,0.00009817642,0.0004905987],"category_scores_gemma":[0.0001758267,0.00007298047,0.0001170293,0.000770607,0.0002357608,0.0001194381,0.0003309188,0.00008596318,0.00007161761],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005983821,"about_ca_system_score_gemma":0.0005428362,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1794775,"about_ca_topic_score_gemma":0.3797255,"domain_scores_codex":[0.9999119,0.00001211449,0.000006708337,0.00002059161,0.00002721999,0.00002151681],"domain_scores_gemma":[0.9998006,0.0000261045,0.00006968099,0.000008108881,0.00005880747,0.00003671713],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00006720328,0.000005808102,0.9929011,0.00001531079,0.00002104148,0.00006566173,0.0004542861,0.0001337637,0.004506255,0.00001785064,0.00003814359,0.001773619],"study_design_scores_gemma":[5.781537e-7,0.000015059,0.9988707,0.000001918432,0.000006726823,0.00002572627,0.0003593539,0.0001591869,0.0003961144,0.000004108449,0.0001597092,8.589566e-7],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9994246,0.00005445936,0.00006545527,0.000004027561,0.000001364105,0.00000224935,0.0001736107,0.000001591757,0.0002727636],"genre_scores_gemma":[0.9992005,0.00007958999,0.0001756235,0.000003552409,0.000004362047,0.000003196779,0.0003165528,0.000001081879,0.0002154616],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1794775,"threshold_uncertainty_score":0.3568656,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008262180663480235,"score_gpt":0.2299896474601176,"score_spread":0.2217274667966374,"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."}}