Thermal heterogeneity in the hyporheic zone of a glacial floodplain
Bibliographic record
Abstract
We examined the thermal regime of surface and hyporheic waters at three kryal sites and four krenal streams within the channel network of a glacial floodplain. Temperature was continuously measured for 1 year in the surface stream and at sediment depths of 30 and 80 cm. The vertical pattern of water temperature was strongly influenced by the direction and intensity of surface water groundwater exchanges. At sites characterized by strong downwelling of surface waters, the thermal regimes of surface and hyporheic waters were virtually identical. In contrast, inputs of groundwater substantially increased mean summer temperatures in the hyporheic zone of the main kryal channel, decreased summer temperatures in the hyporheic zone of krenal streams, and elevated hyporheic temperatures of all stream types during winter. Groundwater from different sources had dramatically different effects on the seasonal regime of temperature in the hyporheic zone. Inflow of shallow alluvial groundwater had minimal effects on seasonal patterns of hyporheic temperature, whereas upwelling from deep alluvial and hillslope aquifers resulted in significant time lags and differences in seasonal amplitudes between surface and hyporheic temperatures. The unexpectedly high thermal heterogeneity of hyporheic waters presumably sustains biodiversity and stimulates ecosystem processes in this glacial floodplain.
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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 | 0.000 | 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 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".