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FRIB Cryomodule Design and Production

2017· article· en· W2775031877 on OpenAlexaff
Ting Xu, Hiroyuki Ao, Brian M. Bird, Nathan Bultman, E. Burkhardt, F. Casagrande, Chris Compton, Jenna Crisp, Kelly Davidson, Kyle Elliott, A. Facco, V. Ganni, Andrei Ganshyn, W. Hartung, K. Hosoyama, Masanori Ikegami, Michael Kelly, P. Knudsen, Robert Laxdal, S. Lidia, Ian Malloch, Samuel Miller, Dan Morris, P. N. Ostroumov, John Popielarski, Laura Popielarski, Marc Reaume, Kenji Saito, Safwan Shanab, Guobao Shen, Mark Shuptar, S. Stark, Jie Wei, John Wenstrom, M. Wiseman, Mengxin Xu, Ying Xu, Yoshishige Yamazaki, Zhihong Zheng

Bibliographic record

VenueJACOW · 2017
Typearticle
Languageen
FieldEngineering
TopicParticle accelerators and beam dynamics
Canadian institutionsTRIUMF
Fundersnot available
KeywordsProduction (economics)Computer scienceEconomics

Abstract

fetched live from OpenAlex

The Facility for Rare Isotope Beams (FRIB), under con-struction at Michigan State University, will utilize a driver linac to accelerate stable ion beams from protons to ura-nium up to energies of >200 MeV per nucleon with a beam power of up to 400 kW. Superconducting technology is widely used in the FRIB project, including the ion sources, linac, and experiment facilities. The FRIB linac consists of 48 cryomodules containing a total of 332 superconducting radio-frequency (SRF) resonators and 69 superconducting solenoids. We report on the design and the construction of FRIB cryomodules.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.012
Threshold uncertainty score0.039

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0120.006

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.022
GPT teacher head0.232
Teacher spread0.210 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreMethods

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2017
Admission routes1
Has abstractyes

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