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Record W2245224556 · doi:10.1103/physrevx.6.031016

Milestones Toward Majorana-Based Quantum Computing

2016· article· en· W2245224556 on OpenAlex

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenuePhysical Review X · 2016
Typearticle
Languageen
FieldPhysics and Astronomy
TopicTopological Materials and Phenomena
Canadian institutionsUniversity of British Columbia
FundersInstitute for Quantum Information and Matter, California Institute of TechnologyWalter Burke Institute for Theoretical PhysicsVetenskapsrådetVillum FondenAspen Center for PhysicsCrafoordska StiftelsenDanmarks GrundforskningsfondCalifornia Institute of TechnologyMicrosoft ResearchDivision of Materials ResearchNatur og Univers, Det Frie ForskningsrådGordon and Betty Moore FoundationNational Research FoundationNatural Sciences and Engineering Research Council of CanadaAlfred P. Sloan FoundationDanmarks Frie ForskningsfondNational Science Foundation
KeywordsQuantum computerSet (abstract data type)MilestoneQuantumReading (process)Quantum informationQuantum information processingQuantum information science

Abstract

fetched live from OpenAlex

Preparing, manipulating, and reading out Majorana zero modes is important for quantum computing. A theoretically developed set of milestone experiments, if conducted successfully, may pave the way for fault-tolerant ``topological'' quantum information processing.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.054
Threshold uncertainty score1.000

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)0.0010.001

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 head0.028
GPT teacher head0.313
Teacher spread0.285 · 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