{"id":"W2135222911","doi":"10.1186/1752-153x-2-14","title":"Graphite furnace atomic absorption spectrometry as a routine method for the quantification of beryllium in blood and serum","year":2008,"lang":"en","type":"article","venue":"Chemistry Central Journal","topic":"Sarcoidosis and Beryllium Toxicity Research","field":"Medicine","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut National de la Recherche Scientifique; Université de Montréal","funders":"Natural Sciences and Engineering Research Council of Canada; Institut de Recherche Robert-Sauvé en Santé et en Sécurité du Travail","keywords":"Chemistry; Detection limit; Beryllium; Magnesium nitrate; Graphite furnace atomic absorption; Reagent; Atomic absorption spectroscopy; Magnesium; Blood serum; Chromatography; Graphite; Mass spectrometry; Certified reference materials; Chelation; Pyrolysis; Nuclear chemistry; Analytical Chemistry (journal); Inorganic chemistry; Organic chemistry","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":[0.0006952088,0.0001209084,0.0002646204,0.00008629418,0.0001331138,0.00002165131,0.000121837,0.0001010688,0.0001261545],"category_scores_gemma":[0.0002013747,0.00008568706,0.0001510899,0.0003152344,0.0001206903,0.00006519234,0.00002423336,0.0004546375,0.000001000257],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006591415,"about_ca_system_score_gemma":0.0001503678,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003252091,"about_ca_topic_score_gemma":0.000002750245,"domain_scores_codex":[0.9987013,0.00003823132,0.0003876948,0.000187277,0.0003228312,0.0003626701],"domain_scores_gemma":[0.9991689,0.0001674993,0.0001814983,0.0001786327,0.0001312117,0.0001722666],"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":[0.0002987907,0.0002127578,0.1351683,0.000124243,0.00009117333,0.00002377802,0.0001704396,0.000007729879,0.8629653,0.00001898853,0.0000929358,0.000825569],"study_design_scores_gemma":[0.002125034,0.00008509977,0.29422,0.00009543911,0.000104659,0.003910598,0.0002380626,0.0005991228,0.6983271,0.0001238993,0.00009526763,0.0000757486],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9939477,0.001641079,0.001783957,0.002259667,0.00004922325,0.0002161777,0.00001125022,0.000007232601,0.00008372794],"genre_scores_gemma":[0.9933119,0.003964965,0.002026025,0.00004916168,0.0002972636,0.000006266896,0.000008320571,0.00001436982,0.000321665],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1646382,"threshold_uncertainty_score":0.3494217,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02976623431239337,"score_gpt":0.3209808436389353,"score_spread":0.2912146093265419,"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."}}