Bibliographic record
Abstract
In the Fall of 2019, the NEWS-G experiment used its latest detector, a 140 cm diameter Spherical Proportional Counter (SPC) to search for low-mass dark matter at the Laboratoire souterrain de Modane (LSM) in France. The detector has then been moved to SNOLAB in Canada and has taken data since the Fall of 2022. SPCs are metallic spheres filled with gas, with a high-voltage anode at the centre that attracts and amplifies ionization charges from atomic recoils. Having the sphere filled with pure methane, hydrogen was used as the target to produce new limits on the proton spin-dependent cross-section around masses of 1 GeV. This paper first introduces the NEWS-G experiment and describes the commissioning at the LSM with the shielding used, the SPC detection principle and the new multi-anode sensor. It then focuses on the calibrations using a UV laser and argon-37, as well as the background discrimination methods to remove alpha-particle induced events and spurious pulses. Then, it presents the profile likelihood ratio method that was used to derive constraints on WIMP mass and cross-section. Finally, it describes the status of the recent data taken at SNOLAB and mentions future projects.
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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 | 0.005 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.004 |
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".