{"id":"W2901019540","doi":"10.1016/j.envres.2018.11.011","title":"Total, methyl and inorganic mercury concentrations in blood and environmental exposure sources in newcomer women in Toronto, Canada","year":2018,"lang":"en","type":"article","venue":"Environmental Research","topic":"Mercury impact and mitigation studies","field":"Environmental Science","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"Public Health Ontario; University of Toronto","funders":"Health Canada; University of Toronto; Public Health Agency of Canada","keywords":"Mercury (programming language); Methylmercury; Population; Environmental chemistry; MERCURY EXPOSURE; Isotope dilution; Fish consumption; Chemistry; Biomonitoring; Environmental health; Medicine; Bioaccumulation; Biology; Fish <Actinopterygii>","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006214745,0.0004940063,0.00070971,0.001285874,0.00295865,0.001147218,0.001388285,0.0005080979,0.00274738],"category_scores_gemma":[0.001741458,0.000644206,0.0007808115,0.004022331,0.0007557131,0.0003841218,0.001103195,0.000629906,0.0003977997],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.03495803,"about_ca_system_score_gemma":0.02370081,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9970695,"about_ca_topic_score_gemma":0.9981492,"domain_scores_codex":[0.9989321,0.00008363535,0.00009079388,0.0002742847,0.0003468064,0.0002725361],"domain_scores_gemma":[0.9982533,0.0001107229,0.0003187298,0.00005754658,0.000806616,0.0004531792],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001619477,0.00002370243,0.9859934,0.0002065518,0.0001235128,0.0005566297,0.003134788,0.0001219577,0.0005632491,0.0001427441,0.003479311,0.005492206],"study_design_scores_gemma":[0.000008736516,0.00002603883,0.995765,0.00007542219,0.00004859305,0.0001459263,0.00241383,0.0001686462,0.00006722906,0.0000173455,0.001244202,0.00001897582],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9792794,0.004044371,0.0003469466,0.001008861,0.00005409579,0.0001034151,0.01086104,0.0000393134,0.004262593],"genre_scores_gemma":[0.9908018,0.002041301,0.0004368431,0.0003103414,0.0000182449,0.00005057644,0.00264352,0.00001470201,0.003682777],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03495803,"threshold_uncertainty_score":0.2536395,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01886995811742919,"score_gpt":0.2849740142042615,"score_spread":0.2661040560868323,"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."}}