Hydrodynamic Conditions Surrounding Brown Trout and Rainbow Trout Redds
Bibliographic record
Abstract
This study examines the hydrodynamic properties of river spawning fish nests commonly referred to as redd's. Little is known about the hydrodynamic properties, spatial location preference and persistence of such structures, relative to flow complexity and channel morphology under varying flood conditions. Many biological studies and inventories of brown Trout (salmo trutta) and rainbow trout (Oncorhynchus mykiss) have been conducted which identify that redd's are typically found in riffle and run morphologies of gravel bed streams, however, the site specific fluid and sedimentological properties of fish staging locations and nest persistence remain unknown. An approximate 1Km reach of Whitemans Creek in Southern Ontario, Canada has been studied in great detail to elucidate the hydrodynamic properties of redd's immediately after spawning has taken place and throughout a series of higher discharge events while the ova remain in the nests. A Pulse Coherent Acoustic Doppler Profiler (PCADP) was used in conjunction with a 20 cm square sampling grid suspended above a series of redd's, in a non-invasive manner, to measure the boundary layer shear and three dimensional velocity profiles within the limits of each redd and the surrounding region. Three-dimensional velocity profiles have been constructed at each redd which spatially range between 20 – 50 discrete velocity profiles being measured within each nest. Scour chains were installed and pavement samples collected in the region surrounding each redd to characterize the sediment transport processes and tractive force conditions of the channel bed proximal to each redd location. Results are presented for the fall 2006 brown trout run and the spring 2007 rainbow trout run.
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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) | 0.001 | 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".