Global synthesis of subglacial lakes and their changing role in a warming climate
Bibliographic record
Abstract
Subglacial lakes provide habitats for life and can modulate ice flow, basal hydrology, biogeochemical fluxes and geomorphic activity. They have been identified widely beneath the ice sheets of Antarctica and Greenland, and detected beneath the ice caps on Devon Island and Iceland, and beneath small valley glaciers. Past investigations focussed on lakes beneath individual ice masses. A scientific synthesis of different lake populations has not been made, so a unified understanding of the mechanisms controlling subglacial lake formation, dynamics, and interaction with other parts of the Earth system is lacking. Here, we integrate existing, often disparate data into a global database of subglacial lakes, enabling subglacial lake characteristics and dynamics to be classified. We use this assessment to evaluate how subglacial lakes shape microbial ecosystems and influence ice flow, subglacial drainage, sediment transport and biogeochemical fluxes. Through our global perspective, we examine how subglacial lake characteristics and function depend on the hydrologic, dynamic and mass balance regime of the ice mass beneath which they are located. By applying this synoptic understanding and perspective, we propose a conceptual model for how subglacial lakes and their impacts on the broader environment will change in a warming world.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.013 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".