{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,18]],"date-time":"2025-03-18T04:12:01Z","timestamp":1742271121320,"version":"3.40.1"},"reference-count":54,"publisher":"IOP Publishing","issue":"1","license":[{"start":{"date-parts":[[2025,3,17]],"date-time":"2025-03-17T00:00:00Z","timestamp":1742169600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2025,3,17]],"date-time":"2025-03-17T00:00:00Z","timestamp":1742169600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/iopscience.iop.org\/info\/page\/text-and-data-mining"}],"funder":[{"name":"Nuclear Physics Program of the National Science Foundation","award":["PHY- 1812374"],"award-info":[{"award-number":["PHY- 1812374"]}]},{"name":"Department of Energy, Office of Science, Office of Nuclear Physics","award":["DE-FG02- 97ER41041"],"award-info":[{"award-number":["DE-FG02- 97ER41041"]}]}],"content-domain":{"domain":["iopscience.iop.org"],"crossmark-restriction":false},"short-container-title":["Mach. Learn.: Sci. Technol."],"published-print":{"date-parts":[[2025,3,31]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Neutrinoless double-beta decay (<jats:inline-formula>\n                     <jats:tex-math\/>\n                     <mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\" overflow=\"scroll\">\n                        <mml:mrow>\n                           <mml:mn>0<\/mml:mn>\n                           <mml:mi>\u03bd<\/mml:mi>\n                           <mml:mi>\u03b2<\/mml:mi>\n                           <mml:mi>\u03b2<\/mml:mi>\n                        <\/mml:mrow>\n                     <\/mml:math>\n                  <\/jats:inline-formula>) is a rare nuclear process that, if observed, will provide insight into the nature of neutrinos and help explain the matter-antimatter asymmetry in the Universe. The large enriched germanium experiment for neutrinoless double-beta decay (LEGEND) will operate in two phases to search for <jats:inline-formula>\n                     <jats:tex-math\/>\n                     <mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\" overflow=\"scroll\">\n                        <mml:mrow>\n                           <mml:mn>0<\/mml:mn>\n                           <mml:mi>\u03bd<\/mml:mi>\n                           <mml:mi>\u03b2<\/mml:mi>\n                           <mml:mi>\u03b2<\/mml:mi>\n                        <\/mml:mrow>\n                     <\/mml:math>\n                  <\/jats:inline-formula>. The first (second) stage will employ 200 (1000) kg of High-Purity Germanium (HPGe) enriched in <jats:sup>76<\/jats:sup>Ge to achieve a half-life sensitivity of 10<jats:sup>27<\/jats:sup> (10<jats:sup>28<\/jats:sup>) years. In this study, we present a semi-supervised data-driven approach to remove non-physical events captured by HPGe detectors powered by a novel artificial intelligence model. We utilize affinity propagation to cluster waveform signals based on their shape and a support vector machine to classify them into different categories. We train, optimize, and test our model on data taken from a natural abundance HPGe detector installed in the Full Chain Test experimental stand at the University of North Carolina at Chapel Hill. We demonstrate that our model yields a maximum sacrifice of physics events of <jats:inline-formula>\n                     <jats:tex-math\/>\n                     <mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\" overflow=\"scroll\">\n                        <mml:mrow>\n                           <mml:msubsup>\n                              <mml:mn>0.024<\/mml:mn>\n                              <mml:mrow>\n                                 <mml:mo>\u2212<\/mml:mo>\n                                 <mml:mn>0.003<\/mml:mn>\n                              <\/mml:mrow>\n                              <mml:mrow>\n                                 <mml:mo>+<\/mml:mo>\n                                 <mml:mn>0.004<\/mml:mn>\n                              <\/mml:mrow>\n                           <\/mml:msubsup>\n                           <mml:mi mathvariant=\"normal\">%<\/mml:mi>\n                        <\/mml:mrow>\n                     <\/mml:math>\n                  <\/jats:inline-formula> after data cleaning. Our model is being used to accelerate data cleaning development for LEGEND-200 and will serve to improve data cleaning procedures for LEGEND-1000.<\/jats:p>","DOI":"10.1088\/2632-2153\/adbb37","type":"journal-article","created":{"date-parts":[[2025,2,27]],"date-time":"2025-02-27T22:54:16Z","timestamp":1740696856000},"page":"015064","update-policy":"https:\/\/doi.org\/10.1088\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Machine learning-powered data cleaning for LEGEND: a semi-supervised approach using affinity propagation and support vector machines"],"prefix":"10.1088","volume":"6","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0073-5512","authenticated-orcid":true,"given":"E","family":"Le\u00f3n","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4844-9339","authenticated-orcid":false,"given":"A","family":"Li","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7892-8691","authenticated-orcid":false,"given":"M A","family":"Bahena Schott","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0009-0008-5828-1745","authenticated-orcid":false,"given":"B","family":"Bos","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0009-0002-9336-3937","authenticated-orcid":false,"given":"M","family":"Busch","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0009-0004-9815-2981","authenticated-orcid":false,"given":"J R","family":"Chapman","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0009-0001-3047-478X","authenticated-orcid":false,"given":"G L","family":"Duran","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3777-2237","authenticated-orcid":true,"given":"J","family":"Gruszko","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8651-2960","authenticated-orcid":false,"given":"R","family":"Henning","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5008-1596","authenticated-orcid":false,"given":"E L","family":"Martin","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0342-0217","authenticated-orcid":false,"given":"J F","family":"Wilkerson","sequence":"additional","affiliation":[]}],"member":"266","published-online":{"date-parts":[[2025,3,17]]},"reference":[{"article-title":"LEGEND-1000 preconceptual design report","year":"2021","author":"Abgrall","key":"mlstadbb37bib1"},{"key":"mlstadbb37bib2","doi-asserted-by":"publisher","DOI":"10.1103\/RevModPhys.95.025002","article-title":"Toward the discovery of matter creation with neutrinoless \u03b2\u03b2 decay","volume":"95","author":"Agostini","year":"2023","journal-title":"Rev. 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