Bibliographic record
Abstract
Abstract Subglacial drainage can occur wherever ice at a glacier bed reaches the pressure melting point. The subglacial drainage system is fed from a mixture of surface, englacial, subglacial, and groundwater sources that differ in terms of their spatial distribution and characteristic patterns of temporal variability. Subglacial drainage systems are not readily accessible, and knowledge of their characteristics is derived from a range of indirect methods including radio‐echo sounding, the use of artificial tracers, monitoring, and manipulation of subglacial conditions via boreholes, and monitoring of glacial runoff properties. Subglacial water flow is driven by gradients in hydraulic potential, and occurs through either fast/channelized or slow/distributed systems located at the ice‐bed interface, or through subglacial aquifers. Water can be stored subglacially in cavities, in the pore space of subglacial sediments, or in subglacial lakes. Drainage system structure evolves continually on various timescales in response to changing water inputs, evolving glacier geometry, and changes in glacier flow dynamics. Major hydrological events in such systems include the spring and fall transitions, outburst floods, and structural changes related to glacier advances and glacier surging. In the absence of variable water inputs from the glacier surface, subglacial drainage systems may be sensitive to forcing by earth, ocean, and atmospheric tides.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| 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) | 0.043 | 0.006 |
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".