{"id":"W3194295085","doi":"","title":"Advances in NCS bulk isotope analysis: getting more with less","year":2020,"lang":"en","type":"article","venue":"AGU Fall Meeting Abstracts","topic":"Nuclear Physics and Applications","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Thermo Fisher Scientific (Canada)","funders":"","keywords":"Isotope; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01070798,0.001733471,0.002106448,0.003059234,0.0009956098,0.004648564,0.00363159,0.00286282,0.02144964],"category_scores_gemma":[0.01307822,0.0008943386,0.001180933,0.001858047,0.003646129,0.01078171,0.004713716,0.004472988,0.007604952],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002151554,"about_ca_system_score_gemma":0.002607821,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00569977,"about_ca_topic_score_gemma":0.01188494,"domain_scores_codex":[0.9952492,0.0009319246,0.0001953446,0.0009728349,0.002403904,0.0002468316],"domain_scores_gemma":[0.9853671,0.004184615,0.0005953391,0.002647915,0.006456492,0.0007486278],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001722812,0.0004963643,0.01608833,0.003851932,0.0004157104,0.0003908874,0.001122934,0.003914244,0.2680491,0.06429877,0.09637204,0.5432768],"study_design_scores_gemma":[0.0002434415,0.001253602,0.009951301,0.001130815,0.0003959821,0.00247823,0.001728062,0.0218285,0.176629,0.109309,0.6745664,0.0004857641],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1003138,0.1527569,0.4952337,0.1233278,0.0176736,0.000408236,0.0035939,0.01205122,0.0946408],"genre_scores_gemma":[0.3021868,0.06148234,0.5158911,0.03486242,0.01119389,0.0003533375,0.005062835,0.005862734,0.06310447],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02144964,"threshold_uncertainty_score":0.07175612,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01218721296337396,"score_gpt":0.2489684891578694,"score_spread":0.2367812761944955,"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."}}