Atmospheric pressure influencing ebullition and turbidity
Bibliographic record
Abstract
Methane ebullition from lake sediment is an important source of atmospheric methane. Previous studies have suggested that temperature variations, water level changes, atmospheric pressure fluctuations and wind-induced current can affect ebullition. However, most of those studies were conducted during open-water season. There is a lack of observations during ice-cover, despite of the abundance of seasonally ice-covered lakes. In this dataset, we present high-frequency ebullition intensity data, atmospheric pressure data, bottom-water temperature data, and turbidite data from Base Mine Lake (57° 1' N, 111° 37' W in Alberta, Canada) during ice cover. During the study period, the water level in the lake is stable. Also, due to the ice cover, the impact of wind-induced current is negligible. The dataset shows that ebullition during ice cover is regulated by atmospheric pressure variations; the stable bottom-water temperature has on correlation with the ebullition. The dataset also shows that turbidity at depth in the lake increases during ebullition events.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.018 | 0.026 |
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".