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The Influence of Cooldown Conditions at Transition Temperature on the Quality Factor of Niobium Sputtered Quarter-Wave Resonators for HIE-ISOLDE

2015· article· en· W2559422092 on OpenAlexaboutno aff
Pei Zhang, G. Rosaz, A. Sublet, Mathieu Therasse, Walter Venturini Delsolaro

Bibliographic record

VenueCERN Document Server (European Organization for Nuclear Research) · 2015
Typearticle
Languageen
FieldEngineering
TopicParticle accelerators and beam dynamics
Canadian institutionsnot available
FundersCERN
KeywordsNiobiumQuarter (Canadian coin)ResonatorQuality (philosophy)Materials scienceMetallurgyPhysicsOptoelectronicsGeography

Abstract

fetched live from OpenAlex

Superconducting quarter-wave resonators (QWRs) are to be used in the ongoing linac upgrade of the ISOLDE facility at CERN. The cavities are made of niobium sputtered on copper substrates. They will be operated at 101.28 MHz at 4.5 K providing 6 MV/m accelerating gradient with 10 W power dissipation. In recent measurements, we found the thermal gradient along the cavity during the niobium superconducting transition has an impact on the cavity quality factor. On the other hand, the speed of the cooling down through the superconducting transition turned out to have no influence on the cavity Q-factor.

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)0.001
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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.477
Threshold uncertainty score0.363

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.040
GPT teacher head0.277
Teacher spread0.237 · 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 designBench or experimental
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

Citations2
Published2015
Admission routes1
Has abstractyes

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