{"id":"W3180551516","doi":"10.1111/cobi.13794","title":"Microplastic contamination in Great Lakes fish","year":2021,"lang":"en","type":"article","venue":"Conservation Biology","topic":"Microplastics and Plastic Pollution","field":"Environmental Science","cited_by":95,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ministry of Environment; Ministry of the Environment, Conservation and Parks; University of Toronto","funders":"","keywords":"Microplastics; Environmental science; Abundance (ecology); Contamination; Fish <Actinopterygii>; Population; Aquatic ecosystem; Fishery; Ecology; Environmental chemistry; Biology; Chemistry","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001046595,0.00007072779,0.00009177226,0.00003111137,0.00004529253,0.0000116832,0.00005307399,0.00008646526,0.002368176],"category_scores_gemma":[0.0003045397,0.00007096503,0.00001687455,0.0001979857,0.00009197969,0.00005735598,0.0000476669,0.00006559867,0.000260318],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007855292,"about_ca_system_score_gemma":0.00002530891,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001470493,"about_ca_topic_score_gemma":0.004760938,"domain_scores_codex":[0.9993613,0.00008028336,0.0001682202,0.0001987448,0.00004345063,0.0001480256],"domain_scores_gemma":[0.9996268,0.0001886,0.00004966243,0.00008848884,0.00001671902,0.00002968736],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001972962,0.00005079118,0.6888165,0.00000611945,0.000005079829,0.00001450044,0.00009807756,0.0002168786,0.2887592,0.002600613,0.01462,0.004792484],"study_design_scores_gemma":[0.0006473118,0.00004787612,0.8144515,0.00001578743,0.000007933555,0.00003188182,0.00003048643,0.006413281,0.008516066,0.001473179,0.1681987,0.0001660091],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9866247,0.0000236253,0.009190862,0.001255323,0.0005791209,0.00006377055,0.00002997703,0.00001641714,0.002216259],"genre_scores_gemma":[0.9970137,0.00003066864,0.0005450152,0.001403952,0.0000413257,0.000007643334,0.0001587922,0.000004349256,0.0007945312],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2802432,"threshold_uncertainty_score":0.9985438,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01301867575354475,"score_gpt":0.2190183905724906,"score_spread":0.2059997148189459,"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."}}