{"id":"W4200634628","doi":"10.1103/physrevlett.128.241802","title":"MicroBooNE and the <mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" display=\"inline\"><mml:mrow><mml:msub><mml:mrow><mml:mi>ν</mml:mi></mml:mrow><mml:mrow><mml:mi>e</mml:mi></mml:mrow></mml:msub></mml:mrow></mml:math> Interpretation of the MiniBooNE Low-Energy Excess","year":2022,"lang":"lv","type":"article","venue":"Physical Review Letters","topic":"Astrophysics and Cosmic Phenomena","field":"Physics and Astronomy","cited_by":55,"is_retracted":false,"has_abstract":true,"ca_institutions":"Perimeter Institute","funders":"H2020 Marie Skłodowska-Curie Actions; Science and Technology Facilities Council; Ontario Ministry of Research, Innovation and Science; Government of Canada; Innovation, Science and Economic Development Canada; Harvard University; Ohio State University; Horizon 2020 Framework Programme; Alfred P. Sloan Foundation; U.S. Department of Energy","keywords":"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001259698,0.0007955891,0.0004480606,0.0002048573,0.001382305,0.0008137358,0.002269547,0.0004302113,0.2366692],"category_scores_gemma":[0.0003475923,0.001278903,0.002277677,0.001072241,0.001916801,0.0009358467,0.002495675,0.001601039,0.0005865617],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001576602,"about_ca_system_score_gemma":0.0008619027,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001286467,"about_ca_topic_score_gemma":0.0001773308,"domain_scores_codex":[0.9924541,0.0007161624,0.001629053,0.001487253,0.001962095,0.001751388],"domain_scores_gemma":[0.9934142,0.001351102,0.002317502,0.002161227,0.0001187906,0.0006371426],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001167773,0.0005572981,0.00001157104,0.002207355,0.002196577,0.0002277987,0.002641305,0.002547293,0.008755307,0.6811025,0.2886554,0.009929872],"study_design_scores_gemma":[0.002348445,0.001149214,0.000118187,0.003201552,0.002756466,0.0002312766,0.001774494,0.05275487,0.9273965,0.0004134856,0.006170419,0.001685106],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6496994,0.004350239,0.00245223,0.003816995,0.002044572,0.00007419405,0.0004411261,0.00008868904,0.3370326],"genre_scores_gemma":[0.9856676,0.001938961,0.0004340868,0.006424652,0.002270883,0.001633646,0.0009677729,0.0005147342,0.0001476301],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9186411,"threshold_uncertainty_score":0.9999177,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01128472065739401,"score_gpt":0.2297385369533819,"score_spread":0.2184538162959879,"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."}}