Cryoegg, Cryowurst and Hydrobean: wireless instruments for glaciology and hydrology
Bibliographic record
Abstract
Observations of conditions within and beneath the ice of glaciers and ice sheets are required to better constrain models of glacier dynamics and provide more reliable forecasts of how ice responds to a changing climate. We have developed and deployed two wireless instruments intended to provide long-term observations of englacial and subglacial environments. A third instrument has been developed for use in streams and rivers – this may be used in either glacial or temperate environments.Cryoegg is a spherical instrument deployed in subglacial channels via boreholes, or in moulins. It measures temperature, water pressure and electrical conductivity and provides data live by radio link through the ice to a receiver on the surface. The spherical shape allows it to travel within water channels and report on conditions within the hydrological system. We demonstrate how it has provided 5 months of data from within a glacier moulin in west Greenland, and that the radio link can operate through 2,500m of ice in north-east Greenland.Cryowurst is a cylindrical instrument deployed in a borehole and measures both subglacial hydrological parameters (water pressure, temperature and electrical conductivity) but also its tilt and orientation change as the ice moves. It also reports wirelessly to a datalogger on the glacier surface. It has provided 5 months of data during a deployment in Yukon, Canada.Hydrobean is an instrument intended for citizen scientists studying streams and small rivers in temporate regions. It shares some common technology with the two cryospheric instruments. Hydrobean consists of a hemispherical unit deployed on the river bed, which sends data by radio link to a data logger on the bank. It measures water pressure, water temperature and electrical conductivity and is intended to help identify pollution events (which may raise both the temperature and electrical conductivity of the water). Hydrobean has been tested in the River Usk in Wales and the river Dart in south-west England. We also intend to deploy Hydrobean in supraglacial streams during future glaciological fieldwork.The data loggers which receive the data from all three wireless instruments store the data locally but can also forward data to a web portal using cellular or satellite links. This has allowed us to closely monitor and retrieve data in close to real time and reduces the risk of data loss from equipment damage in a harsh environment.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 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".