MétaCan
Menu
Back to cohort
Record W3196084393 · doi:10.18429/jacow-srf2019-tufua7

Review of Muon Spin Rotation Studies of SRF Materials

2019· article· en· W3196084393 on OpenAlex
Tobias Junginger, Robert Laxdal

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJACOW · 2019
Typearticle
Languageen
FieldEngineering
TopicSuperconducting Materials and Applications
Canadian institutionsTRIUMF
Fundersnot available
KeywordsMuonMuon spin spectroscopyRotation (mathematics)PhysicsNuclear physicsComputer scienceArtificial intelligence

Abstract

fetched live from OpenAlex

Muons spin rotate in magnetic fields and emit a positron preferentially in spin direction after decay. These properties enable muon spin rotation (muSR) as a precise probe for local magnetism. muSR has been used to characterize SRF materials since 2010. At TRIUMF a so called surface beam implants muons at a material dependent depth of about 150 µm in the bulk. A dedicated spectrometer was developed for field of first vortex penetration and pinning strength measurements of SRF materials in parallel magnetic fields of up to 300 mT. A low energy beam available at PSI implants muons at variable depth in the London layer allowing for direct measurements of the London penetration depth from which the lower critical field and the superheating field can be calculated. This facility is limited to parallel magnetic fields of up to 25 mT. Here, surface and low energy muSR results on SRF materials are reviewed and cross-correlated to each other and to further results from additional experiments. Finally, we present the status of a new facility based on the similar beta-NMR technique enabling measurements in the London layer of SRF materials exposed to parallel magnetic fields above 200 mT.

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)0.000
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.297

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.035
GPT teacher head0.306
Teacher spread0.271 · 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