{"id":"W2004314912","doi":"10.1016/j.fct.2007.01.010","title":"Risk and benefits from consuming salmon and trout: A Canadian perspective","year":2007,"lang":"en","type":"article","venue":"Food and Chemical Toxicology","topic":"Aquaculture Nutrition and Growth","field":"Agricultural and Biological Sciences","cited_by":60,"is_retracted":false,"has_abstract":false,"ca_institutions":"Institut National de Santé Publique du Québec; Université Laval; Centre hospitalier universitaire de Québec","funders":"Ministère de la Santé et des Services sociaux","keywords":"Trout; Fishery; Brown trout; Nutrient; Mercury (programming language); Fish farming; Aquaculture; Fish <Actinopterygii>; Toxicology; Biology; Ecology","routes":{"ca_aff":true,"ca_fund":true,"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":[],"consensus_categories":[],"category_scores_codex":[0.00006952419,0.00009246293,0.0001349801,0.00001002448,0.0001363399,0.00002363578,0.00003947152,0.0001813909,0.00006066457],"category_scores_gemma":[0.00006197072,0.00004127245,0.00001946063,0.00006467157,0.0001387202,0.00003195222,0.00003035698,0.0001315792,0.000001851979],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002398123,"about_ca_system_score_gemma":0.000004133246,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.009751736,"about_ca_topic_score_gemma":0.1041023,"domain_scores_codex":[0.9993811,0.00001930797,0.00009060146,0.0002463843,0.000041987,0.0002206118],"domain_scores_gemma":[0.9994403,0.0002005404,0.0000287322,0.00001654661,0.00002687741,0.0002870699],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0001796005,0.0001244911,0.1044557,0.000006443019,0.0000766993,0.00002130808,0.001474487,3.080248e-8,0.7970919,0.01059121,0.0006060943,0.08537205],"study_design_scores_gemma":[0.001018498,0.0009059754,0.8900876,0.0000232556,0.00005739547,0.00007720452,0.005654432,0.00001061987,0.0655828,0.01764441,0.01850404,0.0004337805],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9948165,0.001947681,8.083676e-7,0.001835234,0.00001890752,0.00007519216,0.0001668238,0.00001795701,0.001120836],"genre_scores_gemma":[0.9989183,0.0001854514,0.0000848454,0.0006054695,0.0001669295,0.000002630842,0.00002328999,6.470718e-7,0.00001241456],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7856319,"threshold_uncertainty_score":0.9968424,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01378966466768329,"score_gpt":0.2112647143176742,"score_spread":0.1974750496499909,"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."}}