{"id":"W1984295685","doi":"10.1016/j.chemosphere.2007.05.100","title":"Temporal trends and spatial distribution of dioxins and furans in lake trout or lake whitefish from the Canadian Great Lakes","year":2008,"lang":"en","type":"article","venue":"Chemosphere","topic":"Toxic Organic Pollutants Impact","field":"Environmental Science","cited_by":63,"is_retracted":false,"has_abstract":false,"ca_institutions":"Ministry of the Environment, Conservation and Parks; University of Toronto","funders":"U.S. Environmental Protection Agency","keywords":"Coregonus clupeaformis; Trout; Salvelinus; Toxic equivalency factor; Congener; Environmental science; Christian ministry; Fish <Actinopterygii>; Fishery; Polychlorinated dibenzofurans; Lake ecosystem; Salmonidae; Coregonus; Rainbow trout; Persistent organic pollutant; Environmental chemistry; Pollutant; Hydrology (agriculture); Ecology; Chemistry; Biology; Geology; Ecosystem","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":[0.00007749021,0.000132814,0.0001690374,0.000005712012,0.0001302503,0.00001918848,0.0001333345,0.00009512404,0.004230081],"category_scores_gemma":[0.00005550836,0.00009045957,0.0000221623,0.0002226387,0.0003956348,0.0001237416,0.00004743456,0.0001184065,0.00001118244],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001201089,"about_ca_system_score_gemma":0.00005639881,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.1458927,"about_ca_topic_score_gemma":0.995726,"domain_scores_codex":[0.9991701,0.0000289236,0.0001656068,0.000221632,0.0001598087,0.0002539733],"domain_scores_gemma":[0.999543,0.00003888589,0.00005175369,0.0001959003,0.000001309047,0.0001691997],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003453201,0.00001955401,0.925346,0.000001557656,0.000007780571,0.00003103363,0.001121518,0.000002546054,0.0004915662,6.686007e-7,0.001541521,0.07140168],"study_design_scores_gemma":[0.0005724402,0.00003672976,0.9890956,0.00001141774,0.000009830113,0.00003020523,0.0001075495,0.0001209669,0.0006879726,0.00002168826,0.009193074,0.0001125543],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9941896,0.00006370331,0.000012224,0.001226497,0.0000389461,0.00008007584,0.002429513,0.00001298763,0.001946404],"genre_scores_gemma":[0.999006,0.00003030715,0.00004774546,0.0001030779,0.00003464415,0.000001805819,0.00004528012,0.00001079441,0.0007203923],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8498333,"threshold_uncertainty_score":0.9966802,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01148340164670529,"score_gpt":0.2042565515683395,"score_spread":0.1927731499216342,"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."}}