{"id":"W4407400164","doi":"10.1139/facets-2024-0108","title":"Investigating the potential uptake of microplastic-derived carbon into a boreal lake food web using carbon-13 labelled plastic","year":2025,"lang":"en","type":"article","venue":"FACETS","topic":"Microplastics and Plastic Pollution","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lakehead University; Dalhousie University; University of New Brunswick; University of Toronto; Carleton University; Environment and Climate Change Canada; University of Waterloo; Queen's University","funders":"Environment and Climate Change Canada; Natural Sciences and Engineering Research Council of Canada; Mitacs","keywords":"Food web; Boreal; Carbon fibers; Microplastics; Environmental science; Dissolved organic carbon; Environmental chemistry; Oceanography; Ecology; Chemistry; Geology; Materials science; Composite material; Biology; Ecosystem","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000217707,0.0002479663,0.0002696991,0.00007592004,0.0001990328,0.00003863166,0.0002991383,0.0001333433,0.0002127562],"category_scores_gemma":[0.0004169286,0.0001980174,0.00007044894,0.000416947,0.0003963746,0.00004399856,0.0003369405,0.0002475244,0.00001230414],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001159625,"about_ca_system_score_gemma":0.0001356946,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00116107,"about_ca_topic_score_gemma":0.005994841,"domain_scores_codex":[0.9983702,0.00009423499,0.0004502164,0.0003624088,0.0003187644,0.0004042099],"domain_scores_gemma":[0.9991573,0.0002425965,0.0001993129,0.0002752217,0.00002307757,0.0001024593],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003266811,0.00005563647,0.009708271,0.00004390715,0.00006674291,0.000003012446,0.0005463464,0.0222239,0.9663895,0.00007538625,0.00035957,0.0004950704],"study_design_scores_gemma":[0.002442751,0.0003055247,0.1115898,0.0003569981,0.0003867975,0.00002651886,0.0004141746,0.8219725,0.05780565,0.001168609,0.002909736,0.0006209305],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9937858,0.00008095892,0.001681115,0.00008781405,0.00131916,0.0002584467,0.00007541255,0.00003483193,0.002676461],"genre_scores_gemma":[0.9983782,0.000009736948,0.001338388,0.00006220579,0.0000853118,0.000008282614,0.00001386019,0.00001867263,0.00008533693],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9085838,"threshold_uncertainty_score":0.8074915,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008999459000401236,"score_gpt":0.2093080603811821,"score_spread":0.2003086013807809,"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."}}