QuSpin zero-field magnetometer characterization for the TUCAN experiment
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".