Searching for solar axions at the Sudbury Neutrino Observatory
Bibliographic record
Abstract
We explore a novel detection possibility for solar axions, which relies only on their couplings to nucleons, via the axion-induced dissociation of deuterons into their constituent neutrons and protons. An opportune target for this process is the now-concluded Sudbury Neutrino Observatory (SNO) experiment, which relied upon large quantities of heavy water to resolve the solar neutrino problem. From the full SNO dataset we exclude in a model-independent fashion isovector axion-nucleon couplings $|g^3_{aN}|\equiv\frac{1}{2}|g_{an}-g_{ap}|>2\times10^{-5}$GeV${}^{-1}$ at 95 % C.L. for sub-MeV axion masses, covering previously unexplored regions of the axion parameter space. In the absence of a precise cancellation between $g_{an}$ and $g_{ap}$ this result also exceeds comparable constraints from other laboratory experiments, and excludes regions of the parameter space for which astrophysical constraints from SN1987A and neutron star cooling are inapplicable due to axion trapping.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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.
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".