MINER reactor based search for axionlike particles using sapphire ( <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"> <mml:msub> <mml:mtext>Al</mml:mtext> <mml:mn>2</mml:mn> </mml:msub> <mml:msub> <mml:mi mathvariant="normal">O</mml:mi> <mml:mn>3</mml:mn> </mml:msub> </mml:math> ) detectors
Bibliographic record
Abstract
The absence of definitive results for WIMP dark matter has sparked growing interest in alternative dark matter candidates, such as axions and axionlike particles (ALPs), which also provide insight into the strong CP problem. The Mitchell Institute Neutrino Experiment at Reactor (MINER), conducted at the Nuclear Science Center of Texas A&M University, investigated ALPs near a 1 MW h TRIGA nuclear reactor core, positioned approximately 4 m away. This experiment employed cryogenic sapphire detectors with a low detection threshold ( ≈ 100 eV ), equipped with a transition edge sensor capable of detecting athermal phonons. Due to the low-background environment, we were able to exclude ALPs with axion-photon coupling and axion-electron coupling as small as g a γ γ = 10 − 5 and g a e e = 10 − 7 , respectively. Energy depositions below 3 keV were not considered and remain blinded for our coherent elastic neutrino-nucleus scattering analysis. This is the first result demonstrating the MINER experiment’s potential to probe low-mass ALPs, enabled by its low-threshold detector and proximity to a reactor.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.012 | 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".