{"id":"W4280543397","doi":"10.1021/acschemneuro.2c00166","title":"Molecular Fates of Organometallic Mercury in Human Brain","year":2022,"lang":"en","type":"article","venue":"ACS Chemical Neuroscience","topic":"Mercury impact and mitigation studies","field":"Environmental Science","cited_by":32,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Light Source (Canada); University of Saskatchewan","funders":"National Institute of General Medical Sciences; National Institute of Environmental Health Sciences; Canadian Institutes of Health Research; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; Canada Foundation for Innovation; University of Saskatchewan","keywords":"Mercury (programming language); Methylmercury; Environmental chemistry; Bioaccumulation; Chemistry; Mercury poisoning; Toxicity; Environmental toxicology; Physiology; Toxicology; Biology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002194255,0.00008498914,0.0001275417,0.00004140762,0.000120768,0.000008408263,0.0004077652,0.00001410951,0.00078301],"category_scores_gemma":[0.0002194096,0.00008355731,0.0000319963,0.0008155229,0.000421883,0.0001151844,0.0006465612,0.0001380982,0.00001221774],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005388005,"about_ca_system_score_gemma":0.000007437162,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004963301,"about_ca_topic_score_gemma":0.000001651884,"domain_scores_codex":[0.9988339,0.00005353756,0.0001982113,0.0002821338,0.0004108181,0.0002214201],"domain_scores_gemma":[0.9996359,0.00005413053,0.00006521549,0.000179081,0.000003278907,0.0000623529],"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":[0.000001854591,0.00006325776,0.01027533,0.000002118578,4.124315e-7,0.000006701372,0.0001987888,0.0002931744,0.9884318,0.0001737927,0.0003871208,0.0001657078],"study_design_scores_gemma":[0.0001831053,0.00005517867,0.02517025,0.000002072072,0.000002846614,0.000009334419,0.0001081479,0.0001088317,0.9705855,0.000732445,0.00290696,0.0001353389],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9967518,0.00001663181,0.00001901519,0.0006959068,0.00004709993,0.00008948393,0.000005669169,0.00001457608,0.002359746],"genre_scores_gemma":[0.9983615,0.000003222528,0.0000361541,0.001415097,0.000002972578,0.00001805609,0.000002082438,0.000006278256,0.0001546407],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01784626,"threshold_uncertainty_score":0.8573411,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01664309129488687,"score_gpt":0.2623958425615393,"score_spread":0.2457527512666524,"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."}}