{"id":"W2996682374","doi":"10.5194/gchron-2-177-2020","title":"Highly accurate dating of micrometre-scale baddeleyite domains through combined focused ion beam extraction and U–Pb thermal ionization mass spectrometry (FIB-TIMS)","year":2020,"lang":"en","type":"article","venue":"Geochronology","topic":"Geological and Geochemical Analysis","field":"Earth and Planetary Sciences","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University; Royal Ontario Museum; University of Toronto","funders":"Science and Technology Facilities Council; Natural Sciences and Engineering Research Council of Canada; University of Toronto; McMaster University","keywords":"Baddeleyite; Meteorite; Thermal ionization mass spectrometry; Mass spectrometry; Isotope dilution; Analytical Chemistry (journal); Ion; Chemistry; Geology; Materials science; Ionization; Zircon; Geochemistry; Astrobiology; Environmental chemistry; Physics; Chromatography","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000132244,0.0001831236,0.0003761496,0.00009054314,0.0001391168,0.00002949841,0.0001846482,0.0001716072,0.00652694],"category_scores_gemma":[0.0001170471,0.0001466913,0.00008100636,0.0007064316,0.0001983915,0.000254706,0.0000412737,0.0002165057,0.0001077827],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000006499579,"about_ca_system_score_gemma":0.0000195613,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009618394,"about_ca_topic_score_gemma":0.0003539044,"domain_scores_codex":[0.9985801,0.0001043033,0.0003783743,0.000430648,0.0001583503,0.0003482164],"domain_scores_gemma":[0.9992269,0.0002108965,0.0002361699,0.0001511342,0.00006200884,0.000112855],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0003120913,0.00007906707,0.309842,0.00007665285,0.0001596347,0.00001807432,0.0003987387,0.004818551,0.6696219,0.00015146,0.0001754707,0.01434634],"study_design_scores_gemma":[0.001878221,0.001564075,0.7823104,0.00002122351,0.0002083307,0.00002327362,0.0004831661,0.03047612,0.1721414,0.009649938,0.0007051186,0.0005388206],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9886614,0.0004975707,0.006437788,0.002457853,0.00009858963,0.0001250397,0.00006069026,0.00006253765,0.001598519],"genre_scores_gemma":[0.9896513,0.0001350026,0.009258883,0.0003309223,0.0001239543,0.000001286453,0.0004693894,0.000003910486,0.000025382],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4974805,"threshold_uncertainty_score":0.9943812,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01341272056519726,"score_gpt":0.2094725253082756,"score_spread":0.1960598047430783,"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."}}