Cryoegg: development and field trials of a wireless subglacial probe for deep, fast-moving ice
Bibliographic record
Abstract
Abstract Subglacial hydrological systems require innovative technological solutions to access and observe. Wireless sensor platforms can be used to collect and return data, but their performance in deep and fast-moving ice requires quantification. We report experimental results from Cryoegg: a spherical probe that can be deployed into a borehole or moulin and transit through the subglacial hydrological system. The probe measures temperature, pressure and electrical conductivity in situ and returns all data wirelessly via a radio link. We demonstrate Cryoegg's utility in studying englacial channels and moulins, including in situ salt dilution gauging. Cryoegg uses VHF radio to transmit data to a surface receiving array. We demonstrate transmission through up to 1.3 km of cold ice – a significant improvement on the previous design. The wireless transmission uses Wireless M-Bus on 169 MHz; we present a simple radio link budget model for its performance in cold ice and experimentally confirm its validity. Cryoegg has also been tested successfully in temperate ice. The battery capacity should allow measurements to be made every 2 h for more than a year. Future iterations of the radio system will enable Cryoegg to transmit data through up to 2.5 km of ice.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".