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Online quality factor measurement of the SRF cavity in injector cryomodule of VECC electron LINAC

2018· article· en· W2806263264 on OpenAlex
U. Bhunia, Vaishali Naik, Robert Laxdal, Yanyun Ma, Ruslan Nagimov, David Kishi, Vladimir Zvyagintsev

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueIndian Journal of Cryogenics · 2018
Typearticle
Languageen
FieldEngineering
TopicParticle accelerators and beam dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsLinear particle acceleratorInjectorPhysicsQuality (philosophy)ElectronNuclear engineeringNuclear physicsMedical physicsNuclear medicineMedicineOpticsEngineeringBeam (structure)Quantum mechanics

Abstract

fetched live from OpenAlex

The ANURIB facility being planned at VECC will use a super-conducting electron linac (e-Linac) as photo-fission driver. The e-Linac will initially be of 30 MeV, 2 mA with an optional upgrade to 50 MeV planned in the future. An identical e-Linac is being built for the ARIEL project at TRIUMF, Canada. The 30 MeV e-linac is made using three 1.3GHz nine cell niobium cavities of Cornell-type, each cavity supplying 10 MV acceleration. The first 9-cell cavity is housed in a cryomodule called Injector Cryomodule (ICM) followed by an Accelerator Cryo- Module (ACM) comprising two 9-cell cavities. In the first phase, the ICM has been developed in collaboration with TRIUMF. The cavity operates at 1.3 GHz and 2 K. The paper highlights the online quality factor measurement of the ICM using calorimetric method.

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.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.284
Threshold uncertainty score0.385

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 head0.027
GPT teacher head0.275
Teacher spread0.247 · 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