A laboratory method for the visualization and quantification of hyporheic flow paths and velocities
Bibliographic record
Abstract
Hyporheic flow, the flow of water through the permeable material immediately surrounding a river, is important for nutrient cycling, dissolved oxygen transport, and contaminant transport. In addition, there is recent concern regarding the role of hyporheic flow on the contamination of rivers following oil spills. To better understand hyporheic flow paths and velocities, it is important to measure hyporheic flow at high spatial and temporal resolution. A practical method to measure hyporheic flow in a laboratory flume based on dye injection, digital images, and moment analysis was developed. An experiment conducted using a single gravel bar demonstrated good agreement between observations and estimates based on image processing. The measured hyporheic flow field showed upstream and downstream flow that discharged downstream of the bar top, the presence of a flow divide and flow stagnation, and hyporheic flow velocities indicative of turbulent flow for which Darcy’s law is not applicable.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.003 |
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".