Geomorphic controls on hyporheic exchange flow in mountain streams
Bibliographic record
Abstract
Hyporheic exchange flows were simulated using MODFLOW and MODPATH to estimate relative effects of channel morphologic features on the extent of the hyporheic zone, on hyporheic exchange flow, and on the residence time of stream water in the hyporheic zone. Four stream reaches were compared in order to examine the influence of stream size and channel constraint. Within stream reaches, the influence of pool‐step or pool‐riffle sequences, channel sinuosity, secondary channels, and channel splits was examined. Results showed that the way in which channel morphology controlled exchange flows differed with stream size and, in some cases, with channel constraint. Pool‐step sequences drove hyporheic exchange in the second‐order sites, creating exchange flows with relatively short residence times. Multiple features interacted to drive hyporheic exchange flow in the unconstrained fifth‐order site, where pool‐riffle sequences and a channel split created exchange flows with short residence times, whereas a secondary channel created exchange flows with long residence times. There was relatively little exchange flow in the bedrock‐constrained fifth‐order site. Groundwater flow models were effective in examining the morphologic features that controlled hyporheic exchange flow, and surface‐visible channel morphologic features controlled the development of the hyporheic zone in these mountain streams.
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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 | 0.000 | 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".