{"id":"W2995605174","doi":"10.1007/s00216-019-02271-6","title":"Determination of the isotopic composition of lutetium using MC-ICPMS","year":2019,"lang":"en","type":"article","venue":"Analytical and Bioanalytical Chemistry","topic":"Radioactive element chemistry and processing","field":"Chemistry","cited_by":9,"is_retracted":false,"has_abstract":false,"ca_institutions":"National Research Council Canada","funders":"National Institute of Standards and Technology; China Scholarship Council; National Natural Science Foundation of China","keywords":"Lutetium; Fractionation; Isotope; Rhenium; Atomic mass; Analytical Chemistry (journal); Chemistry; NIST; Radiochemistry; Mass spectrometry; Primary standard; Calibration; Environmental chemistry; Chromatography; Nuclear physics; Inorganic chemistry; Physics; 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":[0.0007778684,0.0005753178,0.0005177142,0.001078728,0.0009474659,0.0008571237,0.0009309682,0.000802781,0.001940764],"category_scores_gemma":[0.00165236,0.0002941461,0.0003812232,0.001009051,0.0005912323,0.000541947,0.0004512102,0.000728055,0.0007695415],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008876903,"about_ca_system_score_gemma":0.0009473283,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003535286,"about_ca_topic_score_gemma":0.006257087,"domain_scores_codex":[0.9988725,0.000113867,0.00005085331,0.0002843582,0.0005843479,0.0000941394],"domain_scores_gemma":[0.9994986,0.0001261749,0.00004853471,0.00006712119,0.0002338407,0.00002570072],"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":[0.0001308466,0.00001770937,0.00121236,0.00007036596,0.00002080169,0.00004045512,0.00006009859,0.0001197847,0.9894599,0.0004560871,0.0001943341,0.008217449],"study_design_scores_gemma":[0.000007886943,0.00005521778,0.001774704,0.000008085643,0.00001804769,0.0001393086,0.00002707851,0.001666054,0.9914569,0.0001311843,0.004704614,0.00001085385],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7916169,0.004482302,0.1760099,0.0003328077,0.0002870623,0.0004184053,0.002395487,0.001915365,0.02254187],"genre_scores_gemma":[0.838737,0.001995349,0.1424932,0.0003466989,0.00007625011,0.0002811219,0.001141283,0.0003927612,0.0145363],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003535286,"threshold_uncertainty_score":0.007029474,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01341487558187987,"score_gpt":0.2540679507014673,"score_spread":0.2406530751195874,"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."}}