{"id":"W4386976979","doi":"10.1103/physreva.108.039901","title":"Erratum: Isotope-selective laser ablation ion-trap loading of <mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"><mml:mmultiscripts><mml:mi>Ba</mml:mi><mml:none/><mml:mo>+</mml:mo><mml:mprescripts/><mml:none/><mml:mn>137</mml:mn></mml:mmultiscripts></mml:math> using a <mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"><mml:msub><mml:mtext>BaCl</mml:mtext><mml:mn>2</mml:mn></mml:msub></mml:math> target [Phys. Rev. A <b>105</b>, 033102 (2022)]","year":2023,"lang":"lv","type":"erratum","venue":"Physical review. A/Physical review, A","topic":"Mass Spectrometry Techniques and Applications","field":"Chemistry","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Ion trap; Laser ablation; Hyperfine structure; Physics; Ion; Atomic physics; Library science; Laser; Computer science; Optics","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":[0.00127319,0.001570289,0.0008199957,0.001670528,0.003601099,0.002055414,0.002551241,0.002772518,0.09295547],"category_scores_gemma":[0.006237123,0.001044504,0.0009644052,0.001789131,0.0007650068,0.002388001,0.001246453,0.004586911,0.05459029],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002307794,"about_ca_system_score_gemma":0.002575265,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007340627,"about_ca_topic_score_gemma":0.01808395,"domain_scores_codex":[0.9987729,0.00008071709,0.0001702996,0.0002219965,0.0006165787,0.0001374621],"domain_scores_gemma":[0.9973659,0.000426327,0.0001976629,0.0004324264,0.001391734,0.0001859756],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001117681,0.00003139614,0.0002541413,0.0001802565,0.0000159864,0.0001942835,0.00003815828,0.0001229149,0.003002967,0.001784175,0.9835489,0.01071506],"study_design_scores_gemma":[0.00003745796,0.00004832917,0.001716286,0.0001265982,0.00003877873,0.0002861999,0.0001086919,0.0005692399,0.01290342,0.001395298,0.9827161,0.00005365616],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"editorial","genre_gemma":"other","genre_scores_codex":[0.00750186,0.005202693,0.01475615,0.06475691,0.8165574,0.0002075369,0.02076813,0.005963758,0.06428549],"genre_scores_gemma":[0.06889355,0.01258167,0.03697954,0.04251629,0.0207652,0.0004582422,0.05016436,0.00809285,0.7595483],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.09295547,"threshold_uncertainty_score":0.310967,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02366785105170831,"score_gpt":0.2876752699853268,"score_spread":0.2640074189336185,"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."}}