{"id":"W747365684","doi":"10.1016/j.chemgeo.2015.06.006","title":"Trace element characterization of USGS reference materials by HR-ICP-MS and Q-ICP-MS","year":2015,"lang":"en","type":"article","venue":"Chemical Geology","topic":"Geochemistry and Geologic Mapping","field":"Computer Science","cited_by":56,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto; University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; U.S. Geological Survey","keywords":"Mafic; Trace element; Characterization (materials science); Geology; Mineralogy; Geochemistry; Materials science; Nanotechnology","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":[0.0002964515,0.0001473739,0.000289893,0.00002459722,0.00002773128,0.00002486409,0.000452413,0.0001989864,0.0001531879],"category_scores_gemma":[0.0001660989,0.0001348258,0.00001926957,0.0001152321,0.0001595525,0.0001263446,0.0003590922,0.0001074393,0.00001862679],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000173337,"about_ca_system_score_gemma":0.00003849855,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000322112,"about_ca_topic_score_gemma":5.596374e-7,"domain_scores_codex":[0.9987636,0.00005531475,0.0003410782,0.000406943,0.0001385795,0.0002945243],"domain_scores_gemma":[0.9991605,0.00004775016,0.0001857203,0.0003299254,0.0001425509,0.0001335649],"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":[0.0000158535,0.00004435734,0.0007179098,0.0000367885,0.000008290686,0.000002853407,0.0002140008,9.364651e-7,0.9948424,0.002078692,0.0009547712,0.001083127],"study_design_scores_gemma":[0.0003880691,0.00006877429,0.0009744314,0.00001276632,0.000005556124,0.0000370962,0.00001557378,0.000374323,0.9666244,0.002762296,0.02857503,0.0001616541],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9867616,0.00007465993,0.006981893,0.002720109,0.0001564546,0.0001092072,0.00001181892,0.00005941583,0.003124819],"genre_scores_gemma":[0.996817,0.00002311863,0.001793706,0.0002059908,0.00005637338,0.00001838793,0.0001003937,0.000002673571,0.0009823651],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02821799,"threshold_uncertainty_score":0.5498037,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02540007990229916,"score_gpt":0.2342663277514397,"score_spread":0.2088662478491405,"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."}}