The chemical composition of runoff from Canada Glacier, Antarctica: implications for glacier hydrology duringa cool summer
Bibliographic record
Abstract
Abstract Variations in the chemical composition of subsurface runoff within Canada Glacier, Antarctica, are used to identify the main source waters, which are vertical surfaces, and melt from solar-heated debris within channels, cryoconite holes and pools. The main flow paths are subsurface connections between cryoconite holes, pools and riffles. The latter may become partially disconnected during hard freeze. The chemical composition of runoff at the outlet of Canada Glacier during January 2000 was dominated by Ca2+, HCO3– and sea salt (Na+ and Cl–), and became depleted in sea-salt and non-sea-salt (*) SO42– as the subsurface drainage system in a frozen pool-and-riffle system was flushed and the melting ice surface became depleted of overwinter dry deposited salts. Only during 2 days of hard freeze did sea salt and *SO42– increase in concentration together. Otherwise, sea salt and *SO42– declined while *Ca2+ and HCO3– increased. The latter ions are derived from the chemical weathering of sediment in frozen-topped pools, channels and cryoconite holes. It is inferred that the hydrochemical processes which occur in the vestigial, subsurface drainage system are the elution of ions from ice melt, dilution of these ions downstream by ice melt from vertical surfaces and the dissolution of dust, in subsurface pools, channels and/or cryoconite holes.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".