{"id":"W2060832950","doi":"10.1007/s00216-007-1537-z","title":"Comparative performance study of different sample introduction techniques for rapid and precise selenium isotope ratio determination using multi-collector inductively coupled plasma mass spectrometry (MC-ICP/MS)","year":2007,"lang":"en","type":"article","venue":"Analytical and Bioanalytical Chemistry","topic":"Analytical chemistry methods development","field":"Chemistry","cited_by":30,"is_retracted":false,"has_abstract":false,"ca_institutions":"Trent University","funders":"","keywords":"Analytical Chemistry (journal); Isotope; Inductively coupled plasma mass spectrometry; Chemistry; Mass spectrometry; Accuracy and precision; Inductively coupled plasma; Sample (material); Sample preparation; Chromatography; Plasma; Physics; Nuclear physics","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":[0.0007168286,0.0005420447,0.001053592,0.00013996,0.0002259562,0.0000805349,0.000236087,0.0003856455,0.0003499718],"category_scores_gemma":[0.0008012006,0.0004650813,0.0001493194,0.0005145465,0.0005248204,0.0001612722,0.0001637886,0.0005111915,5.880843e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003434086,"about_ca_system_score_gemma":0.00008623651,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002317074,"about_ca_topic_score_gemma":0.000007817355,"domain_scores_codex":[0.9967242,0.00003659476,0.001089595,0.0009949171,0.0005480068,0.000606698],"domain_scores_gemma":[0.9974655,0.00102331,0.0003316516,0.0003605774,0.0004208025,0.0003981926],"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":[0.001106468,0.001593704,0.01330846,0.001015009,0.0005499754,0.000006164606,0.0002602282,0.000005157482,0.9800183,0.00003822234,0.00001660443,0.002081702],"study_design_scores_gemma":[0.001454899,0.0002243189,0.002254121,0.00005767337,0.0005145369,0.00002505887,0.0009267671,0.2069772,0.7869484,0.00007770086,0.00006235377,0.0004769904],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9147649,0.00004221499,0.08424369,0.00008074533,0.0000243604,0.0004104623,0.00003994095,0.00006610201,0.0003275259],"genre_scores_gemma":[0.9451526,0.00003915889,0.05381409,0.00001015393,0.0003680013,0.00003653416,0.00005033813,0.00003174324,0.0004973264],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.206972,"threshold_uncertainty_score":0.9997801,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04787467723558363,"score_gpt":0.3195326082100975,"score_spread":0.2716579309745139,"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."}}