Bibliographic record
Abstract
We used end‐of‐summer temperature profiles to examine the thermal structure of 86 small (<500 ha) lakes in Killarney Park, Ontario, Canada, during one cool (1997) and two extremely warm years (1998 and 1999). The main effect of the warm years, which had unusually high air temperatures during the spring, relative to the cool year was to create warmer surface waters, shallower mixing depths, and stronger metalimnetic thermal gradients in nearly all lakes. Changes in deep water temperatures differed between clear (DOC < 2 mgL 21 ) and colored (DOC < 4 mg L−1) lakes. During warm years, the volume of cold water (<10°C) was reduced in clear lakes. In colored lakes, deep water temperatures were more stable, and cold water volume actually increased during one warm year. We suggest that clear lakes will be more sensitive than colored lakes to the warming effects of climate change. Because clear lakes exhibit large thermal changes in response to small differences in DOC, they will also be more sensitive to changes in DOC levels associated with altered hydrological inputs, climate change, or acidification.
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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 | 0.001 | 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".