{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001489653,0.0002214939,0.0001443874,0.0008221352,0.0007970971,0.0004251866,0.0001908354,0.0002297999,0.0008574067],"category_scores_gemma":[0.0004166083,0.000241182,0.0001644151,0.000934987,0.0005569211,0.000190114,0.0004698191,0.000116792,0.000118965],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002463007,"about_ca_system_score_gemma":0.001075475,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.3723273,"about_ca_topic_score_gemma":0.5968921,"domain_scores_codex":[0.9998146,0.00001230792,0.00001186312,0.00004747408,0.00008452926,0.00002922942],"domain_scores_gemma":[0.9996697,0.00002378861,0.0001446542,0.00001237798,0.0001030673,0.00004645854],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00009810335,0.000009814559,0.9665383,0.0000628864,0.00003447349,0.0001685148,0.001117203,0.00008187725,0.02793922,0.00002743025,0.0001200158,0.003802088],"study_design_scores_gemma":[9.017536e-7,0.00002443764,0.9991534,0.000003174929,0.000005664676,0.00003579189,0.0001535641,0.00002695092,0.0003711129,0.000004395637,0.0002188739,0.0000016883],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.999134,0.00008829054,0.0000325525,0.00001202374,5.107833e-7,0.000004341086,0.0001462789,0.000002721014,0.0005793088],"genre_scores_gemma":[0.9985633,0.0001605352,0.0001938937,0.00002263097,0.00000154776,0.00001087869,0.0002081305,0.000002310706,0.0008366985],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6276727,"threshold_uncertainty_score":0.7403203,"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."}}