Chemical weathering in a moraine at the ice sheet margin at Kangerlussuaq, western Greenland
Bibliographic record
Abstract
Weathering caused by interaction between glacial sediments and water in exposed moraines needs to be studied to evaluate their possible effects on the global carbon cycle. In this study, moraine ponds, moraine porewaters, and till samples were collected at a moraine adjacent to the Greenland Ice Sheet at Kangerlussuaq. Scanning electron microscopy (SEM) studies of the till show limited evidence of silicate chemical weathering, but the moraine waters have substantial solute concentrations. δ34SSO4 and δ18OSO4 data indicate that the origin of dissolved sulfate is the oxidation of sulfides, in agreement with the SEM observations. The dissolved HCO3−/SO42− molar ratios indicate an uneven balance between sulfuric and carbonic acid weathering; C-isotope data indicate that some of the CO2 originates from organic carbon mineralization. Ion–ion plots provide evidence of carbonate weathering and of the formation of secondary gypsum and calcite through evaporation and (or) cryoconcentration. The 87Sr/86Sr ratios in the waters correlate with the corresponding till samples, supporting the local origin of the dissolved strontium, which is higher in the waters than in the till due to the selective weathering of biotite. The data evidence a large degree of chemical weathering in moraines promoted by large rock–water ratios and by the hydraulic isolation created by the frozen till. The high PCO2 in the studied moraine waters indicates that they may represent a previously underestimated CO2 source.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".