{"id":"W2345626666","doi":"10.1016/j.physletb.2007.04.053","title":"Joint extraction of <mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" altimg=\"si1.gif\" overflow=\"scroll\"><mml:msub><mml:mi>m</mml:mi><mml:mi>s</mml:mi></mml:msub></mml:math> and <mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" altimg=\"si2.gif\" overflow=\"scroll\"><mml:msub><mml:mi>V</mml:mi><mml:mrow><mml:mi>u</mml:mi><mml:mi>s</mml:mi></mml:mrow></mml:msub></mml:math> from hadronic τ decays","year":2007,"lang":"lv","type":"article","venue":"Physics Letters B","topic":"Particle physics theoretical and experimental studies","field":"Physics and Astronomy","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Physics; Algorithm; Particle physics; Lattice (music); Machine learning; Mathematics; Computer science","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":[0.001561485,0.001635855,0.001011961,0.003056966,0.0006463927,0.003094219,0.001282367,0.0007010231,0.004626944],"category_scores_gemma":[0.005159449,0.0007621842,0.001342662,0.003407221,0.0002695833,0.001642705,0.001346751,0.0005725891,0.002854352],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004612672,"about_ca_system_score_gemma":0.001099642,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002502289,"about_ca_topic_score_gemma":0.004893651,"domain_scores_codex":[0.9989435,0.0001928654,0.0001169037,0.0002187654,0.0003931454,0.0001348597],"domain_scores_gemma":[0.9981623,0.0006373872,0.0003121407,0.0004764841,0.0003321421,0.00007955795],"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":[0.001588805,0.0002427809,0.03905561,0.001093261,0.0005929054,0.001149031,0.0008302179,0.04369269,0.193098,0.05875146,0.004370792,0.6555344],"study_design_scores_gemma":[0.0001585667,0.0002612108,0.02993405,0.0001374599,0.0003951864,0.0005920678,0.0003654009,0.5073349,0.39029,0.04823119,0.02202285,0.0002771166],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3608199,0.0004548959,0.6164708,0.000107249,0.0001340946,0.00009900345,0.00369244,0.005702483,0.01251911],"genre_scores_gemma":[0.7709588,0.0005481811,0.2083206,0.00003821177,0.00006327017,0.0001303455,0.009699623,0.001696574,0.008544346],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004626944,"threshold_uncertainty_score":0.01547861,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01783023281377101,"score_gpt":0.2441936788655239,"score_spread":0.2263634460517529,"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."}}