{"id":"W4391954455","doi":"10.1103/physrevc.109.l022501","title":"First direct <mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"><mml:mmultiscripts><mml:mi>Be</mml:mi><mml:mprescripts/><mml:none/><mml:mn>7</mml:mn></mml:mmultiscripts></mml:math> electron-capture <mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"><mml:mi>Q</mml:mi></mml:math>-value measurement toward high-precision searches for neutrino physics beyond the Standard Model","year":2024,"lang":"lv","type":"article","venue":"Physical review. C","topic":"Neutrino Physics Research","field":"Physics and Astronomy","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"TRIUMF; McGill University","funders":"Nuclear Physics; College of Engineering, Michigan State University; Office of Science; Central Michigan University; U.S. Department of Energy; Gordon and Betty Moore Foundation; Michigan State University; National Science Foundation","keywords":"Penning trap; Physics; Electron capture; Analytical Chemistry (journal); Neutrino; Atomic physics; Algorithm; Nuclear physics; Electron; Chemistry; Mathematics","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":[0.001287726,0.001361395,0.0005810177,0.001269945,0.0009005934,0.003187604,0.00185775,0.001270973,0.1566844],"category_scores_gemma":[0.002577156,0.0008728718,0.000721592,0.001344504,0.0005004993,0.002792594,0.001555486,0.001626293,0.1049595],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001212993,"about_ca_system_score_gemma":0.001117179,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004861287,"about_ca_topic_score_gemma":0.01376476,"domain_scores_codex":[0.9990507,0.0001109432,0.00005292812,0.0001904374,0.0005043817,0.00009072044],"domain_scores_gemma":[0.9985287,0.0003538946,0.00008508527,0.0005033807,0.0004447982,0.0000840576],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0005518955,0.0003023402,0.002545292,0.0005437051,0.00007501423,0.0006224395,0.0007897873,0.0005674007,0.1372885,0.03231927,0.6542853,0.1701092],"study_design_scores_gemma":[0.00007539763,0.00008308488,0.002199975,0.00005343475,0.00002060233,0.0002969982,0.0001202535,0.003251703,0.1788303,0.00505418,0.809923,0.0000909783],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.04439597,0.0008163309,0.2603002,0.005147143,0.001726488,0.001006469,0.1036259,0.09465773,0.4883239],"genre_scores_gemma":[0.1316451,0.001558657,0.2350323,0.001807119,0.0004310487,0.0009941467,0.1157603,0.04926344,0.4635079],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.1566844,"threshold_uncertainty_score":0.5241615,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04311068595809325,"score_gpt":0.2959972497039985,"score_spread":0.2528865637459053,"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."}}