{"id":"W2087011922","doi":"10.1002/xrs.952","title":"Detection of mercury in the kidney via source‐excited x‐ray fluorescence","year":2007,"lang":"en","type":"article","venue":"X-Ray Spectrometry","topic":"Mercury impact and mitigation studies","field":"Environmental Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Imaging phantom; Detection limit; Detector; Mercury (programming language); Materials science; Attenuation; In vivo; Optics; Analytical Chemistry (journal); Nuclear medicine; Chemistry; Physics; Medicine; Chromatography; Computer science","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0002712063,0.0002409222,0.0002568303,0.0002947294,0.0002463416,0.0003314366,0.0002602869,0.0004868291,0.00106765],"category_scores_gemma":[0.0002795849,0.0002136495,0.000172681,0.000125901,0.0003538484,0.0002556703,0.0002902771,0.0002551105,0.0002061564],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002957529,"about_ca_system_score_gemma":0.0003750419,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001225692,"about_ca_topic_score_gemma":0.00157208,"domain_scores_codex":[0.9998517,0.00003791058,0.000004025357,0.00003884834,0.00004615713,0.00002128344],"domain_scores_gemma":[0.9998865,0.00004507941,0.00002190952,0.000009054381,0.00002339854,0.00001407362],"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":[0.00008906261,0.000006764283,0.0008814072,0.00003610854,0.000005807678,0.00002866436,0.0000153356,0.00008703343,0.9973885,0.00004607035,0.00004247341,0.001372742],"study_design_scores_gemma":[0.00001133452,0.0001463114,0.005531751,0.000003846541,0.00001696484,0.0003424222,0.00002480509,0.00100624,0.992235,0.00004645843,0.0006256147,0.000009175757],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9503915,0.001414131,0.04635258,0.0001282277,0.00001694016,0.00002274206,0.0001570015,0.0002849566,0.001231898],"genre_scores_gemma":[0.9601098,0.0007209893,0.03580758,0.00009399676,0.000008739392,0.00001940591,0.0002196393,0.00003074633,0.00298909],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001225692,"threshold_uncertainty_score":0.00357163,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009476341318082759,"score_gpt":0.2432162137196248,"score_spread":0.2337398724015421,"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."}}