{"id":"W4392603317","doi":"10.1139/as-2023-0041","title":"The utility of monitoring snow for microplastics in the Arctic: a pilot study from Iqaluktuuttiaq, Nunavut","year":2024,"lang":"en","type":"article","venue":"Arctic Science","topic":"Microplastics and Plastic Pollution","field":"Environmental Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada; Fisheries and Oceans Canada; University of Toronto","funders":"Northern Contaminants Program","keywords":"Microplastics; Snow; Environmental science; Arctic; Transect; Plastic pollution; Contamination; Pollution; Wildlife; Sampling (signal processing); Physical geography; Oceanography; Ecology; Geography; Geology; Meteorology; Biology","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":[0.0007043187,0.0004820403,0.0002895258,0.0005428939,0.002989779,0.0008827434,0.0007367521,0.0003269011,0.0007434088],"category_scores_gemma":[0.0005969116,0.0002993294,0.0002434758,0.0006287466,0.001025275,0.0002854445,0.0006445788,0.0004381961,0.0001349898],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003548286,"about_ca_system_score_gemma":0.003899437,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.7524706,"about_ca_topic_score_gemma":0.9138667,"domain_scores_codex":[0.9995849,0.0001011638,0.00001498896,0.0001248484,0.00009570459,0.00007843316],"domain_scores_gemma":[0.9991735,0.0001291524,0.00009634666,0.00003064275,0.0003903879,0.0001798929],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004871903,0.000509143,0.9401069,0.0001263455,0.00006371001,0.001541328,0.01838565,0.0007407337,0.02550489,0.0001486263,0.0003312,0.01205425],"study_design_scores_gemma":[0.0000196043,0.0005479748,0.9767848,0.00004192557,0.00002963666,0.0002368157,0.01725412,0.001052295,0.002260792,0.00006359447,0.001689472,0.00001895865],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9984028,0.00005774367,0.0002898389,0.00003008792,0.000006971046,0.00008246768,0.0002352393,0.000003649801,0.0008910609],"genre_scores_gemma":[0.9963134,0.0001164364,0.001837924,0.0000663825,0.00000700904,0.0001161916,0.0003246628,0.000007416886,0.001210577],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2475294,"threshold_uncertainty_score":0.4979744,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03223721336225248,"score_gpt":0.2750943801646933,"score_spread":0.2428571668024408,"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."}}