Modeling circulation and seasonal fluctuations in perennially ice‐covered and ice‐walled<scp>L</scp>ake<scp>U</scp>ntersee,<scp>A</scp>ntarctica
Bibliographic record
Abstract
Lake Untersee, Antarctica, is a freshwater perennially ice covered lake bounded along its north by the Anuchin glacier. The Massachusetts Institute of Technology general circulation model, used on a representative wedge‐shaped lake and actual bathymetry for Lake Untersee, produces estimates for circulation and long‐term temperature and mixing trends. Modeled circulation is dominated by an anticyclonic gyre in front of the glacier, with slower flow exhibited around the lake's perimeter, allowing effective mixing throughout most of the lake with time scales of one month. Estimated velocities bound maximal glacial flour particle size at for effective transport throughout the lake, consistent with the sediment's mostly fine composition observed in field studies, and mixing time scales mean nonuniformities in measured concentration likely require recent or ongoing sources. Areas in which large temperature gradients prevent exchange of fluid demonstrate minimal mixing, such as the lake's upper water layers and the anoxic basin in the south, and circulation is consistently slowed in the northern sheltered bay area. Mean flow velocities fluctuate by about one fifth of their magnitude between summer and winter, and the lake's almost homothermal body temperature varies by about one tenth of a degree over the same period. While calculated temperature profiles qualitatively agree with field data, the model's long‐term equilibrium temperature differs substantially, likely due to poor description of heat transfer with the glacier. Model robustness tests show results differ by ∼ 10% when either grid scale or water temperature are halved.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".