Three Dimensional Computational Flow Modeling and High Resolution Flow Surveys for Fisheries Environmental Studies on the Upper Columbia River.
Bibliographic record
Abstract
In the area downstream of hydroelectric plants, river water circulation patterns represent an important environmental parameter for fish habitat. On the Canadian sector of the Columbia River, white sturgeon use deep eddy pools, which occur both as natural habitat and as features immediately downstream of dams. Adult sturgeon exhibit a preference for deeper water habitats, specifically areas having reduced flow speeds, generally < 0.5 m/s (1.6 feet/s). Two particular sturgeon habitat areas are located downstream of the Hugh A. Keenleyside Dam and in the Waneta Eddy, at the confluence of the Columbia and Pend d'Oreille rivers, immediately downstream from the Waneta Dam on the latter river. For the purposes of environmental assessment studies, ASL has conducted detailed flow measurements downstream of both these dams. These studies have involved a two pronged approach: (1) development and implementation of a three-dimensional, finite-difference hydrodynamic computational model capable of resolving complex eddy patterns and vertical shears in river flows; and (2) field measurement methodologies based on acoustic doppler current profiling instrumentation and real-time high accuracy navigation systems, through which maps of the river circulation, in three dimensions, can be obtained over periods of about one hour. Both the computational modeling and field measurement procedures allow high resolution representation of the full three dimensional flow field to scales ranging from 5 to 25 m in the horizontal and about 1 m in the vertical. High resolution field measurement data sets are used to calibrate, and separately, validate the computational models for the plant discharges in effect during the measurement programs. The computational model can then be applied to determining t...
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".