{"id":"W2072104754","doi":"10.1016/j.fct.2009.09.016","title":"Total mercury determination in different tissues of broiler chicken by using cloud point extraction and cold vapor atomic absorption spectrometry","year":2009,"lang":"en","type":"article","venue":"Food and Chemical Toxicology","topic":"Mercury impact and mitigation studies","field":"Environmental Science","cited_by":64,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"National Centre of Excellence in Analytical Chemistry, University of Sindh; National Research Council Canada","keywords":"Mercury (programming language); Atomic absorption spectroscopy; Environmental chemistry; Chemistry; Cold vapour atomic fluorescence spectroscopy; Broiler; Mass spectrometry; Analytical Chemistry (journal); Chromatography; Food science; Physics; Computer science","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001259843,0.0005266754,0.0003121703,0.0008678822,0.0006913336,0.0002972106,0.0002654683,0.0003916938,0.0006086525],"category_scores_gemma":[0.0001491219,0.0003061762,0.0002497192,0.0003664783,0.0004799147,0.0002810715,0.000187465,0.0003790102,0.0002062334],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003046615,"about_ca_system_score_gemma":0.0004891374,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01285314,"about_ca_topic_score_gemma":0.02358785,"domain_scores_codex":[0.9998586,0.000009137933,0.000008812228,0.00006372559,0.00003719396,0.0000224826],"domain_scores_gemma":[0.9998277,0.00003379212,0.00002370477,0.00001448875,0.00007437077,0.00002589012],"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":[0.0002124623,0.00000990851,0.002306451,0.00003246565,0.00001647515,0.00003365427,0.00004068013,0.00004552332,0.9960854,0.00002414373,0.00001744507,0.00117544],"study_design_scores_gemma":[0.00001824014,0.0004824902,0.05842397,0.00000950811,0.0001007719,0.0003346625,0.0001151827,0.000651887,0.9388351,0.0000749195,0.0009412505,0.00001206044],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9905674,0.001152765,0.005945995,0.00004653164,0.00002696592,0.0000369282,0.000615279,0.00007324701,0.001535007],"genre_scores_gemma":[0.9766977,0.001334004,0.01262889,0.0001214627,0.0000201064,0.00006526299,0.001693198,0.00006062626,0.007378613],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01285314,"threshold_uncertainty_score":0.02555668,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01308034559751198,"score_gpt":0.2683107740647164,"score_spread":0.2552304284672044,"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."}}