Linking the thermal regimes of streams in the Great Lakes Basin, Ontario, to landscape and climate variables
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract The lack of geographically broad‐scale temperature data has limited our ability to classify stream temperatures and assess the processes affecting them. Continuous data (1 July 2005–30 June 2006) from 90 sites throughout the Great Lakes Basin (GLB) were used to classify and model the thermal regimes of streams in Ontario. Existing and newly developed temperature metrics were used to characterize the data for each site. The 90 sites clustered into three thermal regimes based on maximum weekly maximum temperature (°C) and spring rate of change (°C · d −1 ). The centroids of regime 1, 2 and 3 had temperatures of 26.4, 28.4, 23.5°C and warming rates of 0.20, 0.12 and 0.10°C · d −1 , respectively. There was a regional pattern in the thermal regimes; most sites in the north were regime 1 and most sites in the south were regime 2 but neither regime was limited to those areas. Regime 3 sites were found throughout the study area. Discriminant function analysis indicated that per cent riparian forest, mean annual air temperature, per cent surface water and groundwater discharge potential influenced the thermal regimes at the sites, and demonstrated how variables at three spatial scales influence stream temperatures. This study provides a framework for thermal assessments elsewhere and demonstrates how anthropogenic activities such as riparian deforestation, groundwater withdrawal, stream regulation and climate change will all affect the main drivers of thermal regimes in streams. Copyright © 2009 John Wiley & Sons, Ltd.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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) | 0.000 | 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 it