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Record W4403628660 · doi:10.1088/1361-6501/ad89e6

QuSpin zero-field magnetometer characterization for the TUCAN experiment

2024· article· en· W4403628660 on OpenAlexafffund
Michael Zhao, R. Mammei, Derek Fujimoto

Bibliographic record

VenueMeasurement Science and Technology · 2024
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAtomic and Subatomic Physics Research
Canadian institutionsUniversity of WinnipegUniversity of British ColumbiaTRIUMF
FundersJapan Society for the Promotion of ScienceNatural Sciences and Engineering Research Council of CanadaCanada Research ChairsCanada Foundation for Innovation
KeywordsMagnetometerCharacterization (materials science)Zero (linguistics)Field (mathematics)PhysicsMagnetic fieldMathematicsOpticsQuantum mechanicsPure mathematicsPhilosophy

Abstract

fetched live from OpenAlex

Abstract The TUCAN neutron electric dipole moment experiment utilizes the QuSpin Zero-Field Magnetometer (QZFM) to accurately map residual fields within a large magnetically shielded room. Three potential flaws of the QZFM are characterized in preparation for mapping. The magnetometer’s intrinsic offset was measured to be within ± 3 nT and stable over a period of one year. The response was shown to be within 2 percent of linearity in the zero-field regime, up to 2 nT pp , and then follows a smooth dispersion curve. Crosstalk effects induced by multisensor operation were determined to have a small effect, and inconsequential with a separation above 6 cm. These results enable the QZFM for accurate measurement of DC fields, increase the operational range of QZFM by a factor of more than an order of magnitude, and allow for higher efficiency and flexibility by green-lighting simultaneous operation of multiple QZFMs.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.020
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0110.002

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 head0.033
GPT teacher head0.305
Teacher spread0.272 · 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 source (direct Gemma or distilled Codex), 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

Citations3
Published2024
Admission routes2
Has abstractyes

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