Thermal regime of lakes in the Polish Lowlands in the light of climate change
Bibliographic record
Abstract
Based on data on surface water temperature, summer thermal structure and ice phenomena in lakes in northern Poland for the years 1961-2020, changes in their thermal regime during the period of climate change were determined. The average annual surface water temperatures in all lakes (13 lakes) were characterized by an average positive trend at the level of 0.044oC·year-1 with 0.015 oC·year-1 in January and 0.069 oC·year-1 in May. In turn, in the summer (from 20 July to 20 August), the average water temperature within the epilimnion (to a depth of 5 m) was characterized by a positive trend at the level of 0.05–0.07 oC·year-1, while below this layer a negative trend was noted in all lakes. A characteristic feature observed in all lakes was a decrease in the thickness of the epilimnion with a trend at the level of 0.07–0.11 m·year-1. The hypolimnion layer showed a negative trend for its water temperature, which ranged from 0.02oC·year-1 (Raduńskie Górne) to 0.07oC·year-1 (Miedwie). The ice cover appeared on average in the middle of the third decade of December and its trend was characterized by negative values (0.1-0.2 days∙year-1). In turn, the dates of its disappearance were recorded earlier and earlier, most often in the second decade of March. The consequence of the initial and final dates with ice cover is the length of its occurrence, which was shortened on average by 0.7-0.8 days∙year-1. The general trend of shortening the period with ice cover was also accompanied by a clear decrease in its thickness (with a trend of (0.2-0.4 cm∙year-1).
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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 | 0.000 | 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) | 0.000 | 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".