Impact of Hole-ice Calibration on High Energy Event Reconstruction with the IceCube Upgrade
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The IceCube Upgrade, currently under construction at the geographic South Pole, is the next development stage of the IceCube detector. It will consist of seven new columns of novel optical sensors and advanced calibration devices densely deployed at the centre of the existing array. The sensors are frozen into the ice in boreholes created by hot water drilling. The refreezing forms hole ice around modules with optical properties that differ from the surrounding glacial ice. A key objective of the IceCube Upgrade is to enhance our understanding of the optical properties of both bulk ice and refrozen hole ice. Precise ice modelling is crucial for the directional reconstruction of TeV-PeV neutrinos, as resolutions at such high energies can be strongly impacted by uncertainties in ice properties and optical sensor response. An improved directional reconstruction performance will translate to a boost in neutrino source sensitivities using IceCube data collected over the last 12 years. In this contribution, we present the expected improvements in reconstruction performance resulting from advances in hole-ice modelling and the resulting impact on IceCube's sensitivity to astrophysical neutrino sources across three distinct event samples.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it