{"id":"W3127790658","doi":"10.3390/toxics9020027","title":"Assessment of In Vitro Bioaccessibility and In Vivo Oral Bioavailability as Complementary Tools to Better Understand the Effect of Cooking on Methylmercury, Arsenic, and Selenium in Tuna","year":2021,"lang":"en","type":"article","venue":"Toxics","topic":"Mercury impact and mitigation studies","field":"Environmental Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Agriculture and Agri-Food Canada; Université de Montréal; Université du Québec à Montréal","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Bioavailability; Methylmercury; Chemistry; In vivo; Selenium; Food science; Arsenic; Tuna; Ingestion; Meal; Ex vivo; Gadus; Bioaccumulation; Environmental chemistry; In vitro; Biochemistry; Pharmacology; Fish <Actinopterygii>; Biotechnology; Biology; Fishery","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":[0.0007845224,0.0005173649,0.000367086,0.000258614,0.0002423007,0.0005286316,0.0001749109,0.0004928831,0.001084817],"category_scores_gemma":[0.0005579412,0.0002128857,0.0003510632,0.0002519586,0.0003201881,0.0003448614,0.0002333173,0.0007378415,0.0002292843],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003644608,"about_ca_system_score_gemma":0.0003503523,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002805331,"about_ca_topic_score_gemma":0.003926792,"domain_scores_codex":[0.9995781,0.0001883039,0.00002874307,0.00007666207,0.0000831189,0.00004503491],"domain_scores_gemma":[0.9996533,0.0001274762,0.00007199003,0.00005617062,0.00007050946,0.00002051569],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0003945654,0.0001135378,0.002221882,0.00009385452,0.00002826003,0.00003453864,0.0000742626,0.0002013836,0.9947078,0.00005739964,0.00004039197,0.002032066],"study_design_scores_gemma":[0.00001745738,0.002986745,0.02608191,0.00001928162,0.0001137839,0.000151082,0.0001865099,0.001731929,0.9665532,0.0001043788,0.002037435,0.00001620936],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9814029,0.004557735,0.01144988,0.0001628643,0.00005197349,0.00008198472,0.0006310096,0.00004105533,0.001620658],"genre_scores_gemma":[0.9811095,0.003740687,0.01047495,0.0001516011,0.00003359601,0.0001601845,0.0007243024,0.00002859589,0.003576572],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002805331,"threshold_uncertainty_score":0.005578041,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03480310603250503,"score_gpt":0.3372435441488213,"score_spread":0.3024404381163163,"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."}}