{"id":"W4414488811","doi":"10.1021/acsestwater.5c00080","title":"Fractionation of Anthropogenic Particles (Microplastics and Microfibers) along a 2200 km Transect of Canadian Sediments","year":2025,"lang":"en","type":"article","venue":"ACS ES&T Water","topic":"Microplastics and Plastic Pollution","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba; Ministry of the Environment, Conservation and Parks; Environment and Climate Change Canada; University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; Faculty of Arts and Sciences; Ministère de l’Environnement, de la Protection de la nature et des Parcs; Crown-Indigenous Relations and Northern Affairs Canada; Fisheries and Oceans Canada; Environment and Climate Change Canada; University of Toronto; ArcticNet","keywords":"Transect; Microplastics; Bay; Arctic; Settling; Fractionation; Pollution; 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":[0.0001313081,0.0004874376,0.0001793275,0.002295381,0.00217291,0.0009270436,0.0004307825,0.0002674272,0.0009874513],"category_scores_gemma":[0.0003571949,0.0002032765,0.0002673337,0.002213325,0.0006009993,0.0002496506,0.0005990983,0.0002266742,0.0001849882],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.008547369,"about_ca_system_score_gemma":0.007815279,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9804022,"about_ca_topic_score_gemma":0.992767,"domain_scores_codex":[0.9997274,0.000007206051,0.000008351754,0.00006547155,0.0001104074,0.00008120775],"domain_scores_gemma":[0.9995851,0.00001541148,0.00004676755,0.000008722222,0.0002646267,0.00007945693],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001606023,0.0000385447,0.9240682,0.0001187865,0.00008739143,0.0004641526,0.00362636,0.001083229,0.04092567,0.000357835,0.001071688,0.02799745],"study_design_scores_gemma":[0.000001221883,0.00001085123,0.9960686,0.00001087414,0.00001329608,0.00004052136,0.001087657,0.0003746598,0.001100012,0.000012043,0.001271406,0.000008904502],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9963037,0.0001608711,0.00025192,0.00004523479,0.000004420739,0.00001089916,0.000907901,0.00001926893,0.002295877],"genre_scores_gemma":[0.9967058,0.0002436768,0.0005964898,0.00003715782,0.000002997184,0.000008054448,0.000670718,0.000008692421,0.001726424],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01959777,"threshold_uncertainty_score":0.06201577,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006661735746168885,"score_gpt":0.2009635850448632,"score_spread":0.1943018492986943,"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."}}