{"id":"W2249850330","doi":"10.1103/physrevd.92.114028","title":"Effect of<mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" display=\"inline\"><mml:mi>c</mml:mi><mml:mover accent=\"true\"><mml:mi>c</mml:mi><mml:mo stretchy=\"false\">¯</mml:mo></mml:mover></mml:math>resonances in the branching ratio and forward-backward asymmetry of the decay<mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" display=\"inline\"><mml:mi>B</mml:mi><mml:mo stretchy=\"false\">→</mml:mo><mml:msup><mml:mi>K</mml:mi><mml:mo>*</mml:mo></mml:msup><mml:msup><mml:mi>μ</mml:mi><mml:mo>+</mml:mo></mml:msup><mml:msup><mml:mi>μ</mml:mi><mml:mo>−</mml:mo></mml:msup></mml:math>","year":2015,"lang":"lv","type":"article","venue":"Physical review. D. Particles, fields, gravitation, and cosmology/Physical review. D, Particles, fields, gravitation, and cosmology","topic":"Particle physics theoretical and experimental studies","field":"Physics and Astronomy","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Mount Allison University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Stress (linguistics); Algorithm; Computer science; Database; Speech recognition","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009326942,0.0009128111,0.0007223003,0.0005628416,0.00106868,0.00148506,0.001069658,0.001186326,0.09088966],"category_scores_gemma":[0.002706708,0.0007732287,0.0009225111,0.0003558594,0.0006422373,0.001286475,0.001136524,0.001826852,0.005765216],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001074736,"about_ca_system_score_gemma":0.0008843152,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005635877,"about_ca_topic_score_gemma":0.005924438,"domain_scores_codex":[0.9992041,0.0001139041,0.00002561134,0.0002454194,0.0001335605,0.0002774815],"domain_scores_gemma":[0.9980752,0.001104387,0.0001833028,0.0002083803,0.0001572119,0.0002714763],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.01787813,0.002221643,0.008959535,0.001838643,0.0005409947,0.001806969,0.00120879,0.02755948,0.8177325,0.04331239,0.03318435,0.04375653],"study_design_scores_gemma":[0.0009754928,0.001774362,0.03354583,0.0002722624,0.0007480083,0.000738484,0.001220184,0.06283013,0.8502151,0.01131927,0.03604623,0.0003146097],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8325827,0.001617894,0.009198051,0.001699315,0.0008229345,0.00008703881,0.003984787,0.002292357,0.147715],"genre_scores_gemma":[0.9700945,0.0004729043,0.003244857,0.0005872391,0.00004253049,0.00004590099,0.001156742,0.001493122,0.02286203],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09088966,"threshold_uncertainty_score":0.3040562,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01597331113146621,"score_gpt":0.2823607263605095,"score_spread":0.2663874152290433,"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."}}