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000625304 005__ 20250416150454.0
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000625304 0247_ $$2arXiv$$aarXiv:2406.12881
000625304 0247_ $$2datacite_doi$$a10.3204/PUBDB-2025-01092
000625304 037__ $$aPUBDB-2025-01092
000625304 041__ $$aEnglish
000625304 088__ $$2arXiv$$aarXiv:2406.12881
000625304 088__ $$2Fermilab$$aFERMILAB-CONF-24-0237-AD
000625304 1001_ $$0P:(DE-HGF)0$$aSulc, Antonin$$b0$$eCorresponding author
000625304 245__ $$aTowards unlocking insights from logbooks using AI
000625304 260__ $$c2024
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000625304 500__ $$a5 pages, 1 figure, 15th International Particle Accelerator Conference
000625304 520__ $$aElectronic logbooks contain valuable information about activities and events concerning their associated particle accelerator facilities. However, the highly technical nature of logbook entries can hinder their usability and automation. As natural language processing (NLP) continues advancing, it offers opportunities to address various challenges that logbooks present. This work explores jointly testing a tailored Retrieval Augmented Generation (RAG) model for enhancing the usability of particle accelerator logbooks at institutes like DESY, BESSY, Fermilab, BNL, SLAC, LBNL, and CERN. The RAG model uses a corpus built on logbook contributions and aims to unlock insights from these logbooks by leveraging retrieval over facility datasets, including discussion about potential multimodal sources. Our goals are to increase the FAIR-ness (findability, accessibility, interoperability, and reusability) of logbooks by exploiting their information content to streamline everyday use, enable macro-analysis for root cause analysis, and facilitate problem-solving automation.
000625304 536__ $$0G:(DE-HGF)POF4-621$$a621 - Accelerator Research and Development (POF4-621)$$cPOF4-621$$fPOF IV$$x0
000625304 536__ $$0G:(DE-HGF)2020_InternLabs-0011$$aInternLabs-0011 - HIR3X - Helmholtz International Laboratory on Reliability, Repetition, Results at the most advanced X-ray Sources (2020_InternLabs-0011)$$c2020_InternLabs-0011$$x1
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000625304 650_7 $$2Other$$aAccelerator Physics
000625304 650_7 $$2Other$$amc8-application-of-accelerators-technology-transfer-industrial-relations-and-outreach - MC8: Application of Accelerators, Technology Transfer, Industrial Relations, and Outreach
000625304 650_7 $$2Other$$aMC8.U09 - MC8.U09 Other Applications
000625304 650_7 $$2autogen$$aacceleration
000625304 650_7 $$2autogen$$aoperation
000625304 650_7 $$2autogen$$acontrols
000625304 650_7 $$2autogen$$aembedded
000625304 650_7 $$2autogen$$aelectron
000625304 650_7 $$2autogen$$aelectronics
000625304 650_7 $$2autogen$$atiming
000625304 693__ $$0EXP:(DE-MLZ)NOSPEC-20140101$$5EXP:(DE-MLZ)NOSPEC-20140101$$eNo specific instrument$$x0
000625304 7001_ $$aBien, Alex$$b1
000625304 7001_ $$0P:(DE-H253)PIP1087213$$aEichler, Annika$$b2$$udesy
000625304 7001_ $$aRatner, Daniel$$b3
000625304 7001_ $$aRehm, Florian$$b4
000625304 7001_ $$0P:(DE-H253)PIP1014786$$aMayet, Frank$$b5$$udesy
000625304 7001_ $$aHartmann, Gregor$$b6
000625304 7001_ $$aHoschouer, Hayden$$b7
000625304 7001_ $$0P:(DE-H253)PIP1088102$$aTuennermann, Henrik$$b8$$udesy
000625304 7001_ $$0P:(DE-H253)PIP1095111$$aKaiser, Jan$$b9$$udesy
000625304 7001_ $$aSt. John, Jason$$b10
000625304 7001_ $$aMaldonado, Jennefer$$b11
000625304 7001_ $$aHazelwood, K. J.$$b12
000625304 7001_ $$0P:(DE-H253)PIP1002321$$aKammering, Raimund$$b13$$udesy
000625304 7001_ $$0P:(DE-H253)PIP1013281$$aHellert, Thorsten$$b14$$udesy
000625304 7001_ $$0P:(DE-H253)PIP1007238$$aWilksen, Tim$$b15$$udesy
000625304 7001_ $$aKain, Verena$$b16
000625304 7001_ $$aHu, Wan-Lin$$b17
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000625304 9141_ $$y2024
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