A multi-scale method for identifying groundwater exchanges sustaining critical thermal regimes in streams
Bibliographic record
Abstract
A holistic understanding of heterogeneous groundwater-induced thermal regimes was developed for a Southern Ontario creek using a multi-scale field approach. To better understand the habitat characteristics sustained by the groundwater and surface water exchanges, the relationship between groundwater inputs and stream temperatures were investigated at stream, segment, geomorphic-unit and micro-habitat levels. Continuous point temperature measurements at various locations along the main channel were used to determine seasonal and spatial stream temperature trends and to identify areas of possible groundwater contributions. Methods effective for quantifying and locating groundwater inputs were evaluated, including the velocity-area method, stream temperature surveys and sediment temperature measurements. Sediment temperature mapping of riffle-pool and plane-bed geomorphic units illustrated highly varied substrate temperatures in the plan-view of the creek. The potential application of thermal imaging was also explored and thermal images successfully illustrated a groundwater-sustained micro-habitat. The results demonstrated that these multi-scale field techniques allow for different groundwater–surface water exchange processes to be observed and more effectively capture the complexity of these exchanges than single-level field approaches.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".