Search for relativistic magnetic monopoles with IceCube
Bibliographic record
Abstract
We present the first results in the search for relativistic magnetic monopoles with the IceCube detector, a subsurface neutrino telescope located in the South Polar ice cap containing a volume of $1\text{ }\text{ }{\mathrm{km}}^{3}$. This analysis searches data taken on the partially completed detector during 2007 when roughly $0.2\text{ }\text{ }{\mathrm{km}}^{3}$ of ice was instrumented. The lack of candidate events leads to an upper limit on the flux of relativistic magnetic monopoles of ${\ensuremath{\Phi}}_{90%\mathrm{C}.\mathrm{L}.}\ensuremath{\sim}3\ifmmode\times\else\texttimes\fi{}{10}^{\ensuremath{-}18}\text{ }\text{ }{\mathrm{cm}}^{\ensuremath{-}2}\text{ }{\mathrm{sr}}^{\ensuremath{-}1}\text{ }{\mathrm{s}}^{\ensuremath{-}1}$ for $\ensuremath{\beta}\ensuremath{\ge}0.8$. This is a factor of 4 improvement over the previous best experimental flux limits up to a Lorentz boost $\ensuremath{\gamma}$ below ${10}^{7}$. This result is then interpreted for a wide range of mass and kinetic energy values.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".