{"id":"W1968493922","doi":"10.1016/j.sab.2006.06.014","title":"Corrections for matrix effects in X-ray fluorescence analysis—A tutorial","year":2006,"lang":"en","type":"article","venue":"Spectrochimica Acta Part B Atomic Spectroscopy","topic":"X-ray Spectroscopy and Fluorescence Analysis","field":"Physics and Astronomy","cited_by":142,"is_retracted":false,"has_abstract":false,"ca_institutions":"Geological Survey of Canada","funders":"","keywords":"Matrix (chemical analysis); Calibration; Computer science; X-ray fluorescence; Variable (mathematics); Algorithm; Applied mathematics; Fluorescence; Mathematics; Physics; Statistics; Optics; Chemistry; Mathematical analysis","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003882548,0.0007062241,0.001242179,0.0009426381,0.0004461089,0.0002613793,0.0006755496,0.000177558,0.000859021],"category_scores_gemma":[0.00003265623,0.0007219652,0.001050021,0.002572801,0.0001822404,0.0003794153,0.00008394188,0.0006196259,0.0001407199],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004315414,"about_ca_system_score_gemma":0.0002493975,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001555292,"about_ca_topic_score_gemma":0.0007484257,"domain_scores_codex":[0.9955921,0.0001389786,0.001002574,0.001295386,0.0004634034,0.001507602],"domain_scores_gemma":[0.9979948,0.0003640204,0.0004123569,0.0009196295,0.00009834111,0.0002107991],"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":[0.0006475713,0.001232826,0.2187706,0.0000465473,0.001418249,0.00001159083,0.0001942731,0.000921603,0.5883253,0.1770927,0.01126147,0.00007731136],"study_design_scores_gemma":[0.007621315,0.0007278895,0.07865015,0.000148103,0.005119964,0.000003533804,0.000471466,0.03919491,0.783696,0.07304998,0.008307139,0.003009569],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9288673,0.0001837319,0.06090559,0.0005945807,0.002129404,0.001801916,0.0002070091,0.0003201113,0.004990309],"genre_scores_gemma":[0.9820078,0.00001737543,0.01190153,0.00004092254,0.00395503,0.0004062573,0.0004884657,0.00008105801,0.001101542],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1953707,"threshold_uncertainty_score":0.9995232,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004397969230175176,"score_gpt":0.2567683224190324,"score_spread":0.2523703531888572,"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."}}