{"id":"W1949170326","doi":"10.1139/cjfas-2014-0281","title":"Microplastic pollution in St. Lawrence River sediments","year":2014,"lang":"en","type":"article","venue":"Canadian Journal of Fisheries and Aquatic Sciences","topic":"Microplastics and Plastic Pollution","field":"Environmental Science","cited_by":561,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ministère des Ressources naturelles et des Forêts; McGill University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Microplastics; Benthic zone; Sediment; Pollution; Plastic pollution; Environmental science; Invertebrate; Effluent; Sieve (category theory); Environmental chemistry; Oceanography; Hydrology (agriculture); Geology; Ecology; Biology; Chemistry; Environmental engineering; Geomorphology","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":[0.0001283889,0.0002269336,0.0002099499,0.001096329,0.001097431,0.0008699753,0.0002913215,0.0003108276,0.0007167602],"category_scores_gemma":[0.0003547981,0.0002228112,0.0001293669,0.001492513,0.0003874405,0.0002191665,0.0003339394,0.000174374,0.0001660958],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003131093,"about_ca_system_score_gemma":0.002143439,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.7002776,"about_ca_topic_score_gemma":0.8845588,"domain_scores_codex":[0.9997399,0.00001477846,0.00001553156,0.00005788047,0.0001156131,0.00005633698],"domain_scores_gemma":[0.9994521,0.00003033233,0.0001785224,0.00001225525,0.0002549667,0.00007193195],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00007725079,0.00002663973,0.9589898,0.00005672053,0.00003197828,0.0002131043,0.001094403,0.000259867,0.03100047,0.00004286475,0.0002423262,0.007964551],"study_design_scores_gemma":[0.000001094502,0.00003367474,0.997591,0.000006859843,0.00000664176,0.00006008579,0.0003210309,0.0001456091,0.001322533,0.000005574073,0.000500299,0.000005574742],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9986759,0.0001094533,0.00007162033,0.00001742406,0.000001167317,0.000006125797,0.0003951698,0.000008590272,0.0007145737],"genre_scores_gemma":[0.9977913,0.0001518448,0.000286634,0.00003110524,0.000001842164,0.000009704538,0.000394911,0.000002879109,0.001329799],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2997224,"threshold_uncertainty_score":0.602975,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009638903256628858,"score_gpt":0.1878223085783387,"score_spread":0.1781834053217099,"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."}}