{"id":"W2094615680","doi":"10.1039/a906604g","title":"Matrix interference diagnostics for the automation of inductively coupled plasma mass spectrometry (ICP-MS)","year":2000,"lang":"en","type":"article","venue":"Journal of Analytical Atomic Spectrometry","topic":"Mass Spectrometry Techniques and Applications","field":"Chemistry","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Calibration; Interference (communication); Inductively coupled plasma mass spectrometry; Matrix (chemical analysis); Analytical Chemistry (journal); Chemistry; Mass spectrometry; Inductively coupled plasma; Standard addition; Chromatography; Detection limit; Computer science; Plasma; Physics; Statistics; Mathematics; Telecommunications","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009522247,0.001606727,0.0008973553,0.00142779,0.0007584853,0.001740025,0.002112368,0.001286294,0.001277671],"category_scores_gemma":[0.01660058,0.001003342,0.001166213,0.001167501,0.001314351,0.001566567,0.001445568,0.001836841,0.001504391],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001064952,"about_ca_system_score_gemma":0.001675717,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001527422,"about_ca_topic_score_gemma":0.003258959,"domain_scores_codex":[0.9861746,0.003246493,0.0007177908,0.001381285,0.008271682,0.0002080671],"domain_scores_gemma":[0.9925702,0.003207123,0.0008796795,0.001033695,0.002225132,0.00008419817],"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":[0.0003559624,0.0001640147,0.00709321,0.0009127388,0.0001010959,0.0002576971,0.00030178,0.005146335,0.809298,0.006374514,0.002497091,0.1674976],"study_design_scores_gemma":[0.0000559859,0.0008536362,0.003624529,0.00008944593,0.000133309,0.002880893,0.00009234142,0.07358765,0.8856792,0.00395089,0.02898232,0.00006977333],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01589747,0.0009821036,0.9779979,0.0002592332,0.0001999325,0.0002567142,0.00007813751,0.002601322,0.001727169],"genre_scores_gemma":[0.09289254,0.0009252118,0.9038247,0.0003773797,0.00005819662,0.000311361,0.0001743547,0.0002266255,0.001209566],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.009522247,"threshold_uncertainty_score":0.05035907,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01616258614897507,"score_gpt":0.2879893301477553,"score_spread":0.2718267439987802,"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."}}