The Metabolic Balance of Lake Superior's Mixed Layer
Bibliographic record
Abstract
Abstract Understanding carbon (C) dynamics in large lake ecosystems poses challenges due to their size, causing uncertainty in their contribution to the global C cycle. Here, we used autonomous underwater vehicles to calculate upper mixed‐column (UMC) metabolism in Lake Superior. We paired 7 years of high‐resolution dissolved oxygen and temperature data from 17 glider missions with in situ meteorological data to calculate daily gross primary production, ecosystem respiration, and net ecosystem metabolism. We found the UMC of Lake Superior to be net heterotrophic (primary production < ecosystem respiration) most of the time, suggesting its role as a net source of CO 2 to the atmosphere. Heterotrophy was pronounced during cold and transitional days (<14°C) and in nearshore regions (<10 km distance from the shore). When scaled, our results indicate that Lake Superior released 84–112 Tg CO 2 y −1 , which is twice the rate of C it fixes from the UMC itself.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".