{"id":"W2909323451","doi":"10.1016/j.chemosphere.2018.12.139","title":"Dioxins in Great Lakes fish: Past, present and implications for future monitoring","year":2019,"lang":"en","type":"article","venue":"Chemosphere","topic":"Toxic Organic Pollutants Impact","field":"Environmental Science","cited_by":17,"is_retracted":false,"has_abstract":false,"ca_institutions":"Ministry of the Environment, Conservation and Parks; University of Windsor; University of Toronto","funders":"Government of Ontario","keywords":"Environmental science; Trout; Fish <Actinopterygii>; Fishing; Fishery; Context (archaeology); Geography; Environmental protection; Biology; Archaeology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.0005703051,0.0001498144,0.0001232166,0.0005686604,0.0002803363,0.0004807729,0.0001315917,0.0003182182,0.001087406],"category_scores_gemma":[0.0003434226,0.0001210566,0.0001230036,0.001012807,0.0005894501,0.0003884459,0.0002522969,0.000195258,0.0001640931],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001228505,"about_ca_system_score_gemma":0.0007278662,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04881058,"about_ca_topic_score_gemma":0.118459,"domain_scores_codex":[0.9998997,0.00001929147,0.000006906034,0.00002464893,0.00003019932,0.00001928409],"domain_scores_gemma":[0.9997143,0.00003328031,0.00008286356,0.000009234102,0.0001156818,0.00004466106],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003421056,0.00003819535,0.9473947,0.000117772,0.0000614481,0.0000985766,0.0004467561,0.000442339,0.02507829,0.0002452997,0.000350167,0.02538432],"study_design_scores_gemma":[0.000008691882,0.0002983501,0.9907542,0.00002493858,0.00004361174,0.0001410085,0.0009231897,0.0003852631,0.003610505,0.0002031496,0.003598414,0.000008578126],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9952438,0.002278804,0.0002476211,0.0004028938,0.000009181296,0.000004327336,0.0003538921,0.000005476268,0.001453993],"genre_scores_gemma":[0.9934939,0.002838032,0.0004726292,0.0000803906,0.00001583267,0.000004449511,0.0001559163,0.000001967009,0.002936882],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04881058,"threshold_uncertainty_score":0.09705293,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01053598527577707,"score_gpt":0.2423338816800223,"score_spread":0.2317978964042452,"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."}}