Ice-covered ponds in the Untersee Oasis (East Antarctica): Distribution, chemical composition, and trajectory under a warming climate
Bibliographic record
Abstract
Climate change is impacting lakes and ponds in Antarctica. To that end, we investigated the distribution and chemical composition of ice-covered ponds in Untersee Oasis, East Antarctica. Thirty-nine ponds were inventoried, and the thirteen sampled ponds have low total dissolved solutes (TDS) with a Ca(Na)-SO4 or Na-Cl geochemical facies. Tritium and radiocarbon measurements of the total inorganic carbon (TIC) suggest that the ponds are recharged by modern snowmelt. Hierarchical cluster analysis grouped the ponds based on the amount of potential incoming solar radiation reaching their surface. Ponds receiving higher insolation develop moats or completely lose their ice cover during summer, have lower pH, and higher TDS, δ18O, total inorganic carbon, and δ13CTIC,which suggest CO2 availability is not limiting benthic photosynthetic activity. The ponds that receive lower insolation retain their full ice cover and remain well-sealed to direct exchanges with the atmosphere, have high pH, and lower TDS and TIC, and likely host a CO2-starved benthic microbial ecosystem. Therefore, the state of the ponds’ ice cover evolved their hydrochemistry along different trajectories. The findings can be used to predict the trajectory of the chemical composition of the ponds and effect on biological productivity as the phenology of their ice cover shifts under a warming climate.
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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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".