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Record W3172503865 · doi:10.18429/jacow-srf2019-tufub7

Measurement of Surface Resistance Properties with Coaxial Resonators - Review

2019· article· en· W3172503865 on OpenAlexaboutno aff
HyeKyoung Park, Subashini De Silva, Jean Delayen

Bibliographic record

VenueODU Digital Commons (Old Dominion University) · 2019
Typearticle
Languageen
FieldEngineering
TopicAcoustic Wave Resonator Technologies
Canadian institutionsnot available
Fundersnot available
KeywordsMaterials scienceResonatorAcousticsComputer sciencePhysicsOptoelectronics

Abstract

fetched live from OpenAlex

Achieving ever decreasing surface resistance at higher field in superconducting RF accelerating structures is one of most outstanding developments in modern accelerators. The BCS theory has been used widely to estimate the surface resistance and to direct the technology. However, recent research results show that the behavior of the surface resistance further deviates from the BCS theory. So far the study on surface resistance was performed usually with cavities of single frequency which limited the study of frequency dependent surface resistance. The Center for Accelerator Science at Old Dominion University has designed and built several half wave coaxial cavities to study the frequency, temperature, and RF field dependence of surface resistance. TRIUMF in Canada also joined this line of research using such multi frequency quarter wave and half wave coaxial cavities. This type of multi mode cavity will allow us to systematically study the parameters affecting surface resistance on the same cavity surface. In this paper, we review the results ODU and TRIUMF collected so far and proper analysis methods.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.668
Threshold uncertainty score0.709

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.013
GPT teacher head0.163
Teacher spread0.150 · 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 teacher head, not a consensus.

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

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

Citations1
Published2019
Admission routes1
Has abstractyes

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